Original Research

To the Editor:

Psoriasis is a chronic immune-mediated inflammatory skin disease that affects approximately 2% to 3% of the global population and an estimated 7.5 million adults in the United States.¹ The condition is characterized by recurrent episodes of erythematous scaly plaques driven by dysregulated immune responses, particularly involving the interleukin (IL) 23/T-helper (Th) 17 axis.² Although cutaneous symptoms are the most visible manifestation, psoriasis is a systemic disorder with broad multisystem involvement. Comorbidities include psoriatic arthritis, metabolic syndrome, cardiovascular disease, inflammatory bowel disease, depression, and anxiety.¹ These conditions contribute to a heightened risk for premature mortality, increased health care utilization, and an estimated direct cost burden exceeding $11 billion annually in the United States alone.³ Patients with moderate to severe disease frequently require systemic therapy, and long-term disease control is essential to prevent cumulative inflammatory damage and reduce associated morbidity.⁴

Globally, psoriasis prevalence and disease severity vary by geography, ethnicity, and environmental factors, with higher rates in Northern Europe and North America and lower reported prevalence in East Asia and ­sub-Saharan Africa.⁵ In lower-resource settings, access to advanced therapies is limited, and patients often are treated with less effective or more toxic systemic agents, such as methotrexate or cyclosporine.⁵ These disparities not only affect quality of life but also may influence comorbidity and malignancy patterns, underscoring the importance of studying biologic safety in diverse real-world populations.

Over the past decade, the therapeutic landscape for psoriasis has been transformed by biologic agents targeting specific immune pathways.⁶ Interleukin 17 inhibitors (eg, secukinumab, ixekizumab, brodalumab, bimekizumab) act by neutralizing IL-17A, IL-17F, or the IL-17 receptor, thereby reducing keratinocyte activation, neutrophil recruitment, and downstream cytokine production.⁶ Interleukin 23 inhibitors (eg, guselkumab, risankizumab, tildrakizumab) block the p19 subunit of IL-23, halting the expansion and maintenance of pathogenic Th17 cells.⁶ Ustekinumab, an IL-12/23 inhibitor, targets the shared p40 subunit of IL-12 and IL-23, attenuating both Th1 and Th17 signaling.⁶ These agents achieve rapid, durable skin clearance in a large proportion of patients, improve psoriatic arthritis symptoms, and generally are well tolerated, even with long-term use.⁶

Although efficacy is well established, the immunomodulatory nature of IL inhibitors raises theoretical concerns about malignancy risk. Immune surveillance plays a critical role in detecting and eliminating emerging tumor cells.⁷ Data from other systemic immunosuppressants, such as cyclosporine, show increased risks for certain cancers⁸; however, the IL-17 and IL-23 pathways have dual roles in cancer biology.⁷ In some tumor contexts, these cytokines promote carcinogenesis through angiogenesis, epithelial proliferation, and suppression of antitumor immunity; therefore, inhibiting these pathways could theoretically reduce cancer risk.⁷ The uncertainty around this risk-benefit balance has made malignancy a central consideration for dermatologists, particularly when initiating therapy in patients with a history of cancer or other risk factors.

The perception of malignancy risk can influence patient willingness to start biologics as well as physician prescribing patterns.⁹ Some clinicians opt for alternative therapies in individuals with a personal or family history of cancer despite limited direct evidence of harm from IL inhibitors. Conversely, a reassuring malignancy safety profile may support broader adoption of these therapies, especially in patients requiring lifelong disease control.⁹ Shared decision-making in this context requires robust, real-world evidence that accounts for both common and rare malignancy outcomes.

Randomized controlled trials of IL inhibitors have not demonstrated a consistent malignancy signal, but these studies often are underpowered for rare outcomes and limited by short follow-up durations, typically less than 1 year. They also frequently exclude high-risk populations, limiting generalizability.¹⁰ Observational studies using real-world data can address these gaps by including more diverse patient populations, longer observation windows, and larger sample sizes capable of detecting differences in uncommon outcomes.

The TriNetX Analytics Network (http://www.trinetx.com) offers a unique platform for large-scale, real-world pharmacoepidemiologic research. This federated database aggregates deidentified electronic health record data from more than 100 million patients across the United States and internationally, including at academic medical centers, integrated delivery networks, and community hospitals.⁴ Data contributors refresh their datasets regularly, ensuring near-contemporary representation of prescribing trends and clinical outcomes. Standardized terminology mapping, consistent International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding, and centralized data-quality checks enhance the reliability of analyses. Governance protocols and compliance with the Health Insurance Portability and Accountability Act deidentification standards further ensure ethical use of the data. The breadth and depth of the TriNetX network make it possible to evaluate not only common malignancies but also rare cancer types that smaller studies cannot assess with sufficient statistical power.

We performed a retrospective matched-cohort study, querying data from January 1, 2014, through December 31, 2024, using TriNetX to examine whether IL inhibitor exposure is associated with differences in incident malignancy risk among adults with psoriasis. Patients aged 18 years or older with a psoriasis diagnosis (ICD-10-CM code L40.x) and documented exposure to an IL-17, IL-23, or IL-12/23 inhibitor were eligible. Patients with a prior malignancy diagnosis were excluded to reduce prevalence bias. To ensure that malignancies were incident, we included only those diagnosed at least 1 day after initiation of an IL inhibitor.

The comparison cohort consisted of psoriasis patients without IL inhibitor exposure during their observation period. We used 1:1 propensity score matching based on age, sex, race, and ethnicity, applying a caliper of 0.1 to balance baseline characteristics and minimize demographic confounding. The index date for unexposed patients was randomly assigned within their observation period to align follow-up timing with exposed patients. Outcomes were identified by ICD-10-CM codes grouped by skin, hematologic, and solid-organ malignancies. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with statistical significance set at P<.05. Odds ratios were selected over hazard ratios due to variability in precise follow-up time capture and the primary analytic goal of comparing proportional odds within matched follow-up windows.

Propensity score matching was employed because it is a well-established technique in pharmacoepidemiology to mimic some of the balance achieved in randomized trials. By equating treatment and control groups on measured confounders, matching helps isolate the treatment effect, particularly important in nonrandomized datasets in which prescribing decisions may be influenced by baseline characteristics. Grouping cancers into clinically relevant categories allowed us to assess patterns of association, as some cancer types (eg, melanoma, lymphomas) may have pathophysiologic links to inflammatory pathways targeted by IL inhibitors.

The final cohort included 133,352 patients, with 66,676 in each group. The mean (SD) age was 49.3 (16.0) years, and demographic variables were well balanced after matching. The mean follow-up was approximately 3.8 years. Interleukin 17 inhibitors were the most frequently prescribed, followed by IL-23 inhibitors and ustekinumab. Baseline comorbidities such as cardiovascular disease, diabetes, and obesity were comparable between groups, reducing the likelihood of confounding from these factors.

Interleukin inhibitor exposure was associated with significantly reduced odds of several malignancies (eTable). Among skin cancers, melanoma risk was reduced by 36% (OR, 0.641; 95% CI, 0.534-0.77; P<.0001), basal cell carcinoma by 43% (OR, 0.565; 95% CI, 0.48-0.665; P<.0001), and squamous cell carcinoma by 18% (OR, 0.821; 95% CI, 0.676-0.996; P=.0452). Hematologic malignancies showed similar reductions, with non-Hodgkin lymphoma odds reduced by 35% (OR, 0.646; 95% CI, 0.512-0.815; P=.0002) and Hodgkin lymphoma by 50% (OR, 0.5; 95% CI, 0.292-0.855; P=.0098).

Protective associations also were observed for several solid tumors: lung (OR, 0.528; 95% CI, 0.452-0.617; P<.0001), liver (OR, 0.528; 95% CI, 0.399-0.698; P<.0001), pancreatic (OR, 0.65; 95% CI, 0.49-0.861; P=.0025), breast (OR, 0.663; 95% CI, 0.582-0.754; P<.0001), prostate (OR, 0.543; 95% CI, 0.468-0.629; P<.0001), colorectal (OR, 0.592; 95% CI, 0.414-0.846; P=.0036), colon (OR, 0.466; 95% CI, 0.375-0.579; P<.0001), and oropharyngeal (OR, 0.55; 95% CI, 0.327-0.925; P=.0222) cancers. Cervical cancer (OR, 0.604; 95% CI, 0.381-0.958; P=.0304) and anal cancer (OR, 0.4; 95% CI, 0.224-0.714; P=.0013) also showed significant reductions. Vaginal, vulvar, and penile cancers demonstrated no significant differences, likely due to their low incidence and limited statistical power.

The biological plausibility of these findings is supported by preclinical studies implicating IL-17 and IL-23 in tumor-promoting inflammation.¹¹ These cytokines can recruit myeloid-derived suppressor cells, promote angiogenesis, and facilitate tumor-immune evasion. Inhibition may shift the immune microenvironment toward enhanced tumor surveillance, reduce protumorigenic cytokine signaling, and normalize regulatory T-cell function.¹¹ These mechanisms could explain observed reductions in melanoma, lymphomas, and certain solid tumors.

Our results are consistent with several large registry studies showing no increased cancer incidence in IL inhibitor users and extend prior findings by demonstrating significant reductions in multiple cancer types.¹² The melanoma reduction contrasts with the findings in earlier biologic safety studies, possibly due to our larger sample size, broader geographic representation, and inclusion of multiple IL inhibitor classes.¹³ Similar reductions have not been consistently observed with tumor necrosis factor α inhibitors, which have different immunologic targets and a more complex malignancy safety history.¹⁴

Limitations of our study include the retrospective design, potential misclassification of cancer diagnoses, and lack of data on unmeasured confounders such as sun exposure, smoking, alcohol use, and family cancer history. Surveillance bias is possible, though it would likely bias toward higher, not lower, cancer detection in biologic users. Our mean follow-up period of 3.8 years may not be sufficient for cancers with long latency periods.

If replicated, our findings could have meaningful public health implications. Reassurance regarding malignancy safety may increase patient acceptance and physician confidence in prescribing IL inhibitors, particularly for patients requiring long-term therapy. From a payer perspective, the potential for reduced cancer incidence could translate into substantial cost savings over time, offsetting the high up-front cost of biologics. Additionally, these results may be relevant to other IL inhibitor indications, including psoriatic arthritis, ankylosing spondylitis, and inflammatory bowel disease, in which similar pathophysiologic mechanisms may be at play.

In conclusion, this large matched-cohort study found that IL inhibitor therapy in psoriasis was associated with significantly reduced odds of multiple malignancies, including melanoma, lymphomas, and several solid tumors. These findings contribute to the growing body of real-world evidence supporting the long-term safety of IL inhibitors and underscore the need for continued pharmacovigilance and mechanistic research.

To the Editor:

Psoriasis is a chronic immune-mediated inflammatory skin disease that affects approximately 2% to 3% of the global population and an estimated 7.5 million adults in the United States.¹ The condition is characterized by recurrent episodes of erythematous scaly plaques driven by dysregulated immune responses, particularly involving the interleukin (IL) 23/T-helper (Th) 17 axis.² Although cutaneous symptoms are the most visible manifestation, psoriasis is a systemic disorder with broad multisystem involvement. Comorbidities include psoriatic arthritis, metabolic syndrome, cardiovascular disease, inflammatory bowel disease, depression, and anxiety.¹ These conditions contribute to a heightened risk for premature mortality, increased health care utilization, and an estimated direct cost burden exceeding $11 billion annually in the United States alone.³ Patients with moderate to severe disease frequently require systemic therapy, and long-term disease control is essential to prevent cumulative inflammatory damage and reduce associated morbidity.⁴

Globally, psoriasis prevalence and disease severity vary by geography, ethnicity, and environmental factors, with higher rates in Northern Europe and North America and lower reported prevalence in East Asia and ­sub-Saharan Africa.⁵ In lower-resource settings, access to advanced therapies is limited, and patients often are treated with less effective or more toxic systemic agents, such as methotrexate or cyclosporine.⁵ These disparities not only affect quality of life but also may influence comorbidity and malignancy patterns, underscoring the importance of studying biologic safety in diverse real-world populations.

Over the past decade, the therapeutic landscape for psoriasis has been transformed by biologic agents targeting specific immune pathways.⁶ Interleukin 17 inhibitors (eg, secukinumab, ixekizumab, brodalumab, bimekizumab) act by neutralizing IL-17A, IL-17F, or the IL-17 receptor, thereby reducing keratinocyte activation, neutrophil recruitment, and downstream cytokine production.⁶ Interleukin 23 inhibitors (eg, guselkumab, risankizumab, tildrakizumab) block the p19 subunit of IL-23, halting the expansion and maintenance of pathogenic Th17 cells.⁶ Ustekinumab, an IL-12/23 inhibitor, targets the shared p40 subunit of IL-12 and IL-23, attenuating both Th1 and Th17 signaling.⁶ These agents achieve rapid, durable skin clearance in a large proportion of patients, improve psoriatic arthritis symptoms, and generally are well tolerated, even with long-term use.⁶

Although efficacy is well established, the immunomodulatory nature of IL inhibitors raises theoretical concerns about malignancy risk. Immune surveillance plays a critical role in detecting and eliminating emerging tumor cells.⁷ Data from other systemic immunosuppressants, such as cyclosporine, show increased risks for certain cancers⁸; however, the IL-17 and IL-23 pathways have dual roles in cancer biology.⁷ In some tumor contexts, these cytokines promote carcinogenesis through angiogenesis, epithelial proliferation, and suppression of antitumor immunity; therefore, inhibiting these pathways could theoretically reduce cancer risk.⁷ The uncertainty around this risk-benefit balance has made malignancy a central consideration for dermatologists, particularly when initiating therapy in patients with a history of cancer or other risk factors.

The perception of malignancy risk can influence patient willingness to start biologics as well as physician prescribing patterns.⁹ Some clinicians opt for alternative therapies in individuals with a personal or family history of cancer despite limited direct evidence of harm from IL inhibitors. Conversely, a reassuring malignancy safety profile may support broader adoption of these therapies, especially in patients requiring lifelong disease control.⁹ Shared decision-making in this context requires robust, real-world evidence that accounts for both common and rare malignancy outcomes.

Randomized controlled trials of IL inhibitors have not demonstrated a consistent malignancy signal, but these studies often are underpowered for rare outcomes and limited by short follow-up durations, typically less than 1 year. They also frequently exclude high-risk populations, limiting generalizability.¹⁰ Observational studies using real-world data can address these gaps by including more diverse patient populations, longer observation windows, and larger sample sizes capable of detecting differences in uncommon outcomes.

The TriNetX Analytics Network (http://www.trinetx.com) offers a unique platform for large-scale, real-world pharmacoepidemiologic research. This federated database aggregates deidentified electronic health record data from more than 100 million patients across the United States and internationally, including at academic medical centers, integrated delivery networks, and community hospitals.⁴ Data contributors refresh their datasets regularly, ensuring near-contemporary representation of prescribing trends and clinical outcomes. Standardized terminology mapping, consistent International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding, and centralized data-quality checks enhance the reliability of analyses. Governance protocols and compliance with the Health Insurance Portability and Accountability Act deidentification standards further ensure ethical use of the data. The breadth and depth of the TriNetX network make it possible to evaluate not only common malignancies but also rare cancer types that smaller studies cannot assess with sufficient statistical power.

We performed a retrospective matched-cohort study, querying data from January 1, 2014, through December 31, 2024, using TriNetX to examine whether IL inhibitor exposure is associated with differences in incident malignancy risk among adults with psoriasis. Patients aged 18 years or older with a psoriasis diagnosis (ICD-10-CM code L40.x) and documented exposure to an IL-17, IL-23, or IL-12/23 inhibitor were eligible. Patients with a prior malignancy diagnosis were excluded to reduce prevalence bias. To ensure that malignancies were incident, we included only those diagnosed at least 1 day after initiation of an IL inhibitor.

The comparison cohort consisted of psoriasis patients without IL inhibitor exposure during their observation period. We used 1:1 propensity score matching based on age, sex, race, and ethnicity, applying a caliper of 0.1 to balance baseline characteristics and minimize demographic confounding. The index date for unexposed patients was randomly assigned within their observation period to align follow-up timing with exposed patients. Outcomes were identified by ICD-10-CM codes grouped by skin, hematologic, and solid-organ malignancies. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with statistical significance set at P<.05. Odds ratios were selected over hazard ratios due to variability in precise follow-up time capture and the primary analytic goal of comparing proportional odds within matched follow-up windows.

Propensity score matching was employed because it is a well-established technique in pharmacoepidemiology to mimic some of the balance achieved in randomized trials. By equating treatment and control groups on measured confounders, matching helps isolate the treatment effect, particularly important in nonrandomized datasets in which prescribing decisions may be influenced by baseline characteristics. Grouping cancers into clinically relevant categories allowed us to assess patterns of association, as some cancer types (eg, melanoma, lymphomas) may have pathophysiologic links to inflammatory pathways targeted by IL inhibitors.

The final cohort included 133,352 patients, with 66,676 in each group. The mean (SD) age was 49.3 (16.0) years, and demographic variables were well balanced after matching. The mean follow-up was approximately 3.8 years. Interleukin 17 inhibitors were the most frequently prescribed, followed by IL-23 inhibitors and ustekinumab. Baseline comorbidities such as cardiovascular disease, diabetes, and obesity were comparable between groups, reducing the likelihood of confounding from these factors.

Interleukin inhibitor exposure was associated with significantly reduced odds of several malignancies (eTable). Among skin cancers, melanoma risk was reduced by 36% (OR, 0.641; 95% CI, 0.534-0.77; P<.0001), basal cell carcinoma by 43% (OR, 0.565; 95% CI, 0.48-0.665; P<.0001), and squamous cell carcinoma by 18% (OR, 0.821; 95% CI, 0.676-0.996; P=.0452). Hematologic malignancies showed similar reductions, with non-Hodgkin lymphoma odds reduced by 35% (OR, 0.646; 95% CI, 0.512-0.815; P=.0002) and Hodgkin lymphoma by 50% (OR, 0.5; 95% CI, 0.292-0.855; P=.0098).

Protective associations also were observed for several solid tumors: lung (OR, 0.528; 95% CI, 0.452-0.617; P<.0001), liver (OR, 0.528; 95% CI, 0.399-0.698; P<.0001), pancreatic (OR, 0.65; 95% CI, 0.49-0.861; P=.0025), breast (OR, 0.663; 95% CI, 0.582-0.754; P<.0001), prostate (OR, 0.543; 95% CI, 0.468-0.629; P<.0001), colorectal (OR, 0.592; 95% CI, 0.414-0.846; P=.0036), colon (OR, 0.466; 95% CI, 0.375-0.579; P<.0001), and oropharyngeal (OR, 0.55; 95% CI, 0.327-0.925; P=.0222) cancers. Cervical cancer (OR, 0.604; 95% CI, 0.381-0.958; P=.0304) and anal cancer (OR, 0.4; 95% CI, 0.224-0.714; P=.0013) also showed significant reductions. Vaginal, vulvar, and penile cancers demonstrated no significant differences, likely due to their low incidence and limited statistical power.

The biological plausibility of these findings is supported by preclinical studies implicating IL-17 and IL-23 in tumor-promoting inflammation.¹¹ These cytokines can recruit myeloid-derived suppressor cells, promote angiogenesis, and facilitate tumor-immune evasion. Inhibition may shift the immune microenvironment toward enhanced tumor surveillance, reduce protumorigenic cytokine signaling, and normalize regulatory T-cell function.¹¹ These mechanisms could explain observed reductions in melanoma, lymphomas, and certain solid tumors.

Our results are consistent with several large registry studies showing no increased cancer incidence in IL inhibitor users and extend prior findings by demonstrating significant reductions in multiple cancer types.¹² The melanoma reduction contrasts with the findings in earlier biologic safety studies, possibly due to our larger sample size, broader geographic representation, and inclusion of multiple IL inhibitor classes.¹³ Similar reductions have not been consistently observed with tumor necrosis factor α inhibitors, which have different immunologic targets and a more complex malignancy safety history.¹⁴

Limitations of our study include the retrospective design, potential misclassification of cancer diagnoses, and lack of data on unmeasured confounders such as sun exposure, smoking, alcohol use, and family cancer history. Surveillance bias is possible, though it would likely bias toward higher, not lower, cancer detection in biologic users. Our mean follow-up period of 3.8 years may not be sufficient for cancers with long latency periods.

If replicated, our findings could have meaningful public health implications. Reassurance regarding malignancy safety may increase patient acceptance and physician confidence in prescribing IL inhibitors, particularly for patients requiring long-term therapy. From a payer perspective, the potential for reduced cancer incidence could translate into substantial cost savings over time, offsetting the high up-front cost of biologics. Additionally, these results may be relevant to other IL inhibitor indications, including psoriatic arthritis, ankylosing spondylitis, and inflammatory bowel disease, in which similar pathophysiologic mechanisms may be at play.

In conclusion, this large matched-cohort study found that IL inhibitor therapy in psoriasis was associated with significantly reduced odds of multiple malignancies, including melanoma, lymphomas, and several solid tumors. These findings contribute to the growing body of real-world evidence supporting the long-term safety of IL inhibitors and underscore the need for continued pharmacovigilance and mechanistic research.

To the Editor:

Psoriasis is a chronic immune-mediated inflammatory skin disease that affects approximately 2% to 3% of the global population and an estimated 7.5 million adults in the United States.¹ The condition is characterized by recurrent episodes of erythematous scaly plaques driven by dysregulated immune responses, particularly involving the interleukin (IL) 23/T-helper (Th) 17 axis.² Although cutaneous symptoms are the most visible manifestation, psoriasis is a systemic disorder with broad multisystem involvement. Comorbidities include psoriatic arthritis, metabolic syndrome, cardiovascular disease, inflammatory bowel disease, depression, and anxiety.¹ These conditions contribute to a heightened risk for premature mortality, increased health care utilization, and an estimated direct cost burden exceeding $11 billion annually in the United States alone.³ Patients with moderate to severe disease frequently require systemic therapy, and long-term disease control is essential to prevent cumulative inflammatory damage and reduce associated morbidity.⁴

Globally, psoriasis prevalence and disease severity vary by geography, ethnicity, and environmental factors, with higher rates in Northern Europe and North America and lower reported prevalence in East Asia and ­sub-Saharan Africa.⁵ In lower-resource settings, access to advanced therapies is limited, and patients often are treated with less effective or more toxic systemic agents, such as methotrexate or cyclosporine.⁵ These disparities not only affect quality of life but also may influence comorbidity and malignancy patterns, underscoring the importance of studying biologic safety in diverse real-world populations.

Over the past decade, the therapeutic landscape for psoriasis has been transformed by biologic agents targeting specific immune pathways.⁶ Interleukin 17 inhibitors (eg, secukinumab, ixekizumab, brodalumab, bimekizumab) act by neutralizing IL-17A, IL-17F, or the IL-17 receptor, thereby reducing keratinocyte activation, neutrophil recruitment, and downstream cytokine production.⁶ Interleukin 23 inhibitors (eg, guselkumab, risankizumab, tildrakizumab) block the p19 subunit of IL-23, halting the expansion and maintenance of pathogenic Th17 cells.⁶ Ustekinumab, an IL-12/23 inhibitor, targets the shared p40 subunit of IL-12 and IL-23, attenuating both Th1 and Th17 signaling.⁶ These agents achieve rapid, durable skin clearance in a large proportion of patients, improve psoriatic arthritis symptoms, and generally are well tolerated, even with long-term use.⁶

Although efficacy is well established, the immunomodulatory nature of IL inhibitors raises theoretical concerns about malignancy risk. Immune surveillance plays a critical role in detecting and eliminating emerging tumor cells.⁷ Data from other systemic immunosuppressants, such as cyclosporine, show increased risks for certain cancers⁸; however, the IL-17 and IL-23 pathways have dual roles in cancer biology.⁷ In some tumor contexts, these cytokines promote carcinogenesis through angiogenesis, epithelial proliferation, and suppression of antitumor immunity; therefore, inhibiting these pathways could theoretically reduce cancer risk.⁷ The uncertainty around this risk-benefit balance has made malignancy a central consideration for dermatologists, particularly when initiating therapy in patients with a history of cancer or other risk factors.

The perception of malignancy risk can influence patient willingness to start biologics as well as physician prescribing patterns.⁹ Some clinicians opt for alternative therapies in individuals with a personal or family history of cancer despite limited direct evidence of harm from IL inhibitors. Conversely, a reassuring malignancy safety profile may support broader adoption of these therapies, especially in patients requiring lifelong disease control.⁹ Shared decision-making in this context requires robust, real-world evidence that accounts for both common and rare malignancy outcomes.

Randomized controlled trials of IL inhibitors have not demonstrated a consistent malignancy signal, but these studies often are underpowered for rare outcomes and limited by short follow-up durations, typically less than 1 year. They also frequently exclude high-risk populations, limiting generalizability.¹⁰ Observational studies using real-world data can address these gaps by including more diverse patient populations, longer observation windows, and larger sample sizes capable of detecting differences in uncommon outcomes.

The TriNetX Analytics Network (http://www.trinetx.com) offers a unique platform for large-scale, real-world pharmacoepidemiologic research. This federated database aggregates deidentified electronic health record data from more than 100 million patients across the United States and internationally, including at academic medical centers, integrated delivery networks, and community hospitals.⁴ Data contributors refresh their datasets regularly, ensuring near-contemporary representation of prescribing trends and clinical outcomes. Standardized terminology mapping, consistent International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding, and centralized data-quality checks enhance the reliability of analyses. Governance protocols and compliance with the Health Insurance Portability and Accountability Act deidentification standards further ensure ethical use of the data. The breadth and depth of the TriNetX network make it possible to evaluate not only common malignancies but also rare cancer types that smaller studies cannot assess with sufficient statistical power.

We performed a retrospective matched-cohort study, querying data from January 1, 2014, through December 31, 2024, using TriNetX to examine whether IL inhibitor exposure is associated with differences in incident malignancy risk among adults with psoriasis. Patients aged 18 years or older with a psoriasis diagnosis (ICD-10-CM code L40.x) and documented exposure to an IL-17, IL-23, or IL-12/23 inhibitor were eligible. Patients with a prior malignancy diagnosis were excluded to reduce prevalence bias. To ensure that malignancies were incident, we included only those diagnosed at least 1 day after initiation of an IL inhibitor.

The comparison cohort consisted of psoriasis patients without IL inhibitor exposure during their observation period. We used 1:1 propensity score matching based on age, sex, race, and ethnicity, applying a caliper of 0.1 to balance baseline characteristics and minimize demographic confounding. The index date for unexposed patients was randomly assigned within their observation period to align follow-up timing with exposed patients. Outcomes were identified by ICD-10-CM codes grouped by skin, hematologic, and solid-organ malignancies. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with statistical significance set at P<.05. Odds ratios were selected over hazard ratios due to variability in precise follow-up time capture and the primary analytic goal of comparing proportional odds within matched follow-up windows.

Propensity score matching was employed because it is a well-established technique in pharmacoepidemiology to mimic some of the balance achieved in randomized trials. By equating treatment and control groups on measured confounders, matching helps isolate the treatment effect, particularly important in nonrandomized datasets in which prescribing decisions may be influenced by baseline characteristics. Grouping cancers into clinically relevant categories allowed us to assess patterns of association, as some cancer types (eg, melanoma, lymphomas) may have pathophysiologic links to inflammatory pathways targeted by IL inhibitors.

The final cohort included 133,352 patients, with 66,676 in each group. The mean (SD) age was 49.3 (16.0) years, and demographic variables were well balanced after matching. The mean follow-up was approximately 3.8 years. Interleukin 17 inhibitors were the most frequently prescribed, followed by IL-23 inhibitors and ustekinumab. Baseline comorbidities such as cardiovascular disease, diabetes, and obesity were comparable between groups, reducing the likelihood of confounding from these factors.

Interleukin inhibitor exposure was associated with significantly reduced odds of several malignancies (eTable). Among skin cancers, melanoma risk was reduced by 36% (OR, 0.641; 95% CI, 0.534-0.77; P<.0001), basal cell carcinoma by 43% (OR, 0.565; 95% CI, 0.48-0.665; P<.0001), and squamous cell carcinoma by 18% (OR, 0.821; 95% CI, 0.676-0.996; P=.0452). Hematologic malignancies showed similar reductions, with non-Hodgkin lymphoma odds reduced by 35% (OR, 0.646; 95% CI, 0.512-0.815; P=.0002) and Hodgkin lymphoma by 50% (OR, 0.5; 95% CI, 0.292-0.855; P=.0098).

Protective associations also were observed for several solid tumors: lung (OR, 0.528; 95% CI, 0.452-0.617; P<.0001), liver (OR, 0.528; 95% CI, 0.399-0.698; P<.0001), pancreatic (OR, 0.65; 95% CI, 0.49-0.861; P=.0025), breast (OR, 0.663; 95% CI, 0.582-0.754; P<.0001), prostate (OR, 0.543; 95% CI, 0.468-0.629; P<.0001), colorectal (OR, 0.592; 95% CI, 0.414-0.846; P=.0036), colon (OR, 0.466; 95% CI, 0.375-0.579; P<.0001), and oropharyngeal (OR, 0.55; 95% CI, 0.327-0.925; P=.0222) cancers. Cervical cancer (OR, 0.604; 95% CI, 0.381-0.958; P=.0304) and anal cancer (OR, 0.4; 95% CI, 0.224-0.714; P=.0013) also showed significant reductions. Vaginal, vulvar, and penile cancers demonstrated no significant differences, likely due to their low incidence and limited statistical power.

The biological plausibility of these findings is supported by preclinical studies implicating IL-17 and IL-23 in tumor-promoting inflammation.¹¹ These cytokines can recruit myeloid-derived suppressor cells, promote angiogenesis, and facilitate tumor-immune evasion. Inhibition may shift the immune microenvironment toward enhanced tumor surveillance, reduce protumorigenic cytokine signaling, and normalize regulatory T-cell function.¹¹ These mechanisms could explain observed reductions in melanoma, lymphomas, and certain solid tumors.

Our results are consistent with several large registry studies showing no increased cancer incidence in IL inhibitor users and extend prior findings by demonstrating significant reductions in multiple cancer types.¹² The melanoma reduction contrasts with the findings in earlier biologic safety studies, possibly due to our larger sample size, broader geographic representation, and inclusion of multiple IL inhibitor classes.¹³ Similar reductions have not been consistently observed with tumor necrosis factor α inhibitors, which have different immunologic targets and a more complex malignancy safety history.¹⁴

Limitations of our study include the retrospective design, potential misclassification of cancer diagnoses, and lack of data on unmeasured confounders such as sun exposure, smoking, alcohol use, and family cancer history. Surveillance bias is possible, though it would likely bias toward higher, not lower, cancer detection in biologic users. Our mean follow-up period of 3.8 years may not be sufficient for cancers with long latency periods.

If replicated, our findings could have meaningful public health implications. Reassurance regarding malignancy safety may increase patient acceptance and physician confidence in prescribing IL inhibitors, particularly for patients requiring long-term therapy. From a payer perspective, the potential for reduced cancer incidence could translate into substantial cost savings over time, offsetting the high up-front cost of biologics. Additionally, these results may be relevant to other IL inhibitor indications, including psoriatic arthritis, ankylosing spondylitis, and inflammatory bowel disease, in which similar pathophysiologic mechanisms may be at play.

In conclusion, this large matched-cohort study found that IL inhibitor therapy in psoriasis was associated with significantly reduced odds of multiple malignancies, including melanoma, lymphomas, and several solid tumors. These findings contribute to the growing body of real-world evidence supporting the long-term safety of IL inhibitors and underscore the need for continued pharmacovigilance and mechanistic research.

To the Editor:

The widespread availability and popularity of ChatGPT (OpenAI) have sparked interest in its potential applications within various fields, including medical diagnostics.¹ In dermatology, large language models (LLMs) already are being cited as a possible way to reliably respond to common patient queries and produce concise patient education materials.^2,3 That being said, there is skepticism regarding the technology’s efficacy and reliability in producing accurate treatment plans, with variability among popular LLMs; for example, a recent study by Chau et al⁴ demonstrated that ChatGPT was best at providing specific and accurate information regarding patient-facing responses to questions about 5 dermatologic diagnoses compared to Google Bard (now rebranded as Google Gemini) and Bing AI (now rebranded as Microsoft Copilot), which more often produced inaccurate or nonspecific responses. Google Bard also declined to answer one prompt.⁴ Large language models also have been evaluated in diagnosing skin lesions. In 2024, SkinGPT-4 (a pretrained multimodel LLM developed by Zhou et al⁵) achieved just over 80% accuracy in interpreting images of skin lesions and was considered informative by 82.5% of board-certified dermatologists, demonstrating that LLMs may have the potential to become integrated into clinical practice.⁵

Our study aimed to evaluate the performance of GPT-4o (OpenAI)—a widely accessible, low-cost LLM—in diagnosing dermatologic conditions using the HAM10000 dataset, a well-curated collection of dermatoscopic images developed for training and benchmarking artificial intelligence (AI) algorithms.⁶ HAM10000 comprises images representing 7 distinct skin conditions: actinic keratoses (ak), basal cell carcinoma (bcc), benign keratosis (bk), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv), and vascular skin lesions (vsl), providing a robust platform for multiclass classification assessment. We evaluated GPT-4o using 100 dermatoscopic images per condition to assess diagnostic accuracy, potential biases, and limitations in skin lesion identification. The HAM10000 dataset was selected because it offers a large standardized reference set of dermatoscopic (rather than conventional clinical) images commonly used in dermatologic AI research. GPT-4o was chosen due to its patient-friendly interface, widespread use, and prior reports suggesting greater reliability in skin lesion assessment compared with other LLMs.

One hundred images from each of the 7 dermatologic categories were randomly selected for use in our analysis in 2024. The images were selected by our data scientist (J.C.) through random sampling from the dataset. Each image was separately presented to GPT-4o without any preprocessing or modification alongside 2 prompts designed to evaluate the diagnostic capabilities of GPT-4o. Both prompts included the same list of 7 dermatologic conditions for answer choices but differed in contextual information, where prompt 1 provided patient demographic information and localization of the dermatological condition but prompt 2 did not provide these details (Table). No follow-up questions were presented.

For prompt 1, the confusion matrix showed a strong bias toward detecting mel and bcc, with high true positives (mel, 83%; bcc, 37%)(eFigure 1). This pattern possibly suggests a tendency to favor malignant labels (eg, mel, BCC) when uncertainty is present. Interestingly, df and vsl also had notable true positives (46% and 37%, respectively), which is unexpected for less critical conditions because the model’s correct classifications were uneven across benign lesions. Actinic keratoses and nv showed higher misclassification rates, suggesting the model struggled to distinguish them from other lesions.

As shown in eTable 1, prompt 1 exhibited the highest recall for mel at 0.83 but performed worse in precision (0.242) and specificity (0.567) compared to ak, which had an extremely low recall (0.03) but very high specificity (0.992) and moderate precision score (0.375). The highest precision score was seen with vsl (0.738), which also achieved high scores in specificity (0.982) and accuracy (0.88) and performed moderately well in recall (0.31). All performance metrics are reported as proportions (0-1.0), wherein 1.0 indicates 100.

For prompt 2, the second confusion matrix followed similar trends as prompt 1 but still differed in key areas (eFigure 2). Melanoma detection remained strong (true positives, 95%), while bcc shows slightly fewer true positives (24%). Vascular skin lesions improve in true positives (40%), and df dropped slightly (33%). The model continues to struggle with ak and nv, with notable misclassifications observed across other categories

Similar to prompt 1, prompt 2 achieved its highest recall for mel (0.95%), but demonstrated lower precision (0.223%) and specificity (0.488%) for this class. Prompt 2 also produced the highest accuracy for vascular skin lesions (0.90%). The highest specificity was observed for both bk and ak (0.992% each); however, ak again demonstrated the lowest recall, with a value of 0.01%.

A previous study utilizing a model of binary classification to distinguish between mel and benign dermatologic conditions demonstrated poor performance.¹ Additionally, prior studies have employed a less-strict, open-ended style question approach to examine ChatGPT’s ability to diagnose mel with limited efficacy.⁷ The HAM10000 dataset was specifically selected despite its limitations (including the absence of clinical images and limited diversity in skin tones) due to its comprehensive nature, robust annotation standards, and widespread acceptance in dermatologic AI research. Compared to the Diverse Dermatology Images dataset, which notably lacks skin tone diversity, HAM10000 provides a balanced representation of several dermatologic conditions crucial for multiclass classification tasks, making it suitable for benchmarking AI performance. This study aimed to eliminate these limitations by employing a multiclass classification approach; however, despite this switch, our results indicate continued and major limitations of the diagnostic capabilities of GPT-4o.

In its current form, GPT-4o appeared to demonstrate a clear accuracy bias toward correctly identifying specific and severe dermatologic conditions (eg, mel, bcc) but showed low and variable class-level performance for other categories (eg, ak, nv, df, vsl), with frequent misclassification into melanoma or basal cell carcinoma and low recall for some classes (eTables 1 and 2). This finding emphasized that GPT-4o currently lacks the reliability needed for real-life clinical applications in dermatology, as both binary and multiclass models fail to achieve consistent accurate performance across all skin conditions. Notably, GPT-4o may generate false-positive malignant classifications among patients due to its skew in predicted labels toward labeling benign lesions as malignant.

From the patient perspective, younger individuals may upload images of benign nevi only to unnecessarily fear a mel diagnosis after receiving GPT-4o results. Statistically, younger patients are less likely than older patients to have malignant lesions and more likely to instead present with common vsl or df—lesions that GPT-4o appears likely to identify correctly.⁸ For older users, however, the situation may differ. Beyond ak being misclassified as bcc, older patients also may encounter GPT-4o outputs that mislabel lesions as mel, raising concerns and heightening anxiety. Given the technology’s tendency to overestimate the risk of serious dermatologic conditions, this behavior poses a considerable challenge in its current state and may inadvertently intensify public anxiety around mel.

A notable limitation of our study was that, compared to publicly available datasets, the HAM10000 dataset includes only dermatoscopic images rather than a combination of clinical and dermatoscopic images. Furthermore, the HAM10000 dataset comprises images primarily from White patients, whereas other diverse databases (eg, the Diverse Dermatology Images dataset) may be more suitable for training AI algorithms to accurately diagnose skin lesions in individuals with a variety of skin tones.⁹

Ultimately, our results signal that major advancements in the design and training of LLMs such as GPT-4o are necessary before these systems can be integrated into dermatologic diagnostic decision-making to offer benefit rather than cause harm. Consulting a health care professional rather than relying solely on AI, which might otherwise lead to avoidable stress, unnecessary alarm, and potentially increased health care costs due to unwarranted follow-up and testing, should remain the recommended standard of care for patients suspecting a skin lesion.

To the Editor:

The widespread availability and popularity of ChatGPT (OpenAI) have sparked interest in its potential applications within various fields, including medical diagnostics.¹ In dermatology, large language models (LLMs) already are being cited as a possible way to reliably respond to common patient queries and produce concise patient education materials.^2,3 That being said, there is skepticism regarding the technology’s efficacy and reliability in producing accurate treatment plans, with variability among popular LLMs; for example, a recent study by Chau et al⁴ demonstrated that ChatGPT was best at providing specific and accurate information regarding patient-facing responses to questions about 5 dermatologic diagnoses compared to Google Bard (now rebranded as Google Gemini) and Bing AI (now rebranded as Microsoft Copilot), which more often produced inaccurate or nonspecific responses. Google Bard also declined to answer one prompt.⁴ Large language models also have been evaluated in diagnosing skin lesions. In 2024, SkinGPT-4 (a pretrained multimodel LLM developed by Zhou et al⁵) achieved just over 80% accuracy in interpreting images of skin lesions and was considered informative by 82.5% of board-certified dermatologists, demonstrating that LLMs may have the potential to become integrated into clinical practice.⁵

Our study aimed to evaluate the performance of GPT-4o (OpenAI)—a widely accessible, low-cost LLM—in diagnosing dermatologic conditions using the HAM10000 dataset, a well-curated collection of dermatoscopic images developed for training and benchmarking artificial intelligence (AI) algorithms.⁶ HAM10000 comprises images representing 7 distinct skin conditions: actinic keratoses (ak), basal cell carcinoma (bcc), benign keratosis (bk), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv), and vascular skin lesions (vsl), providing a robust platform for multiclass classification assessment. We evaluated GPT-4o using 100 dermatoscopic images per condition to assess diagnostic accuracy, potential biases, and limitations in skin lesion identification. The HAM10000 dataset was selected because it offers a large standardized reference set of dermatoscopic (rather than conventional clinical) images commonly used in dermatologic AI research. GPT-4o was chosen due to its patient-friendly interface, widespread use, and prior reports suggesting greater reliability in skin lesion assessment compared with other LLMs.

One hundred images from each of the 7 dermatologic categories were randomly selected for use in our analysis in 2024. The images were selected by our data scientist (J.C.) through random sampling from the dataset. Each image was separately presented to GPT-4o without any preprocessing or modification alongside 2 prompts designed to evaluate the diagnostic capabilities of GPT-4o. Both prompts included the same list of 7 dermatologic conditions for answer choices but differed in contextual information, where prompt 1 provided patient demographic information and localization of the dermatological condition but prompt 2 did not provide these details (Table). No follow-up questions were presented.

For prompt 1, the confusion matrix showed a strong bias toward detecting mel and bcc, with high true positives (mel, 83%; bcc, 37%)(eFigure 1). This pattern possibly suggests a tendency to favor malignant labels (eg, mel, BCC) when uncertainty is present. Interestingly, df and vsl also had notable true positives (46% and 37%, respectively), which is unexpected for less critical conditions because the model’s correct classifications were uneven across benign lesions. Actinic keratoses and nv showed higher misclassification rates, suggesting the model struggled to distinguish them from other lesions.

As shown in eTable 1, prompt 1 exhibited the highest recall for mel at 0.83 but performed worse in precision (0.242) and specificity (0.567) compared to ak, which had an extremely low recall (0.03) but very high specificity (0.992) and moderate precision score (0.375). The highest precision score was seen with vsl (0.738), which also achieved high scores in specificity (0.982) and accuracy (0.88) and performed moderately well in recall (0.31). All performance metrics are reported as proportions (0-1.0), wherein 1.0 indicates 100.

For prompt 2, the second confusion matrix followed similar trends as prompt 1 but still differed in key areas (eFigure 2). Melanoma detection remained strong (true positives, 95%), while bcc shows slightly fewer true positives (24%). Vascular skin lesions improve in true positives (40%), and df dropped slightly (33%). The model continues to struggle with ak and nv, with notable misclassifications observed across other categories

Similar to prompt 1, prompt 2 achieved its highest recall for mel (0.95%), but demonstrated lower precision (0.223%) and specificity (0.488%) for this class. Prompt 2 also produced the highest accuracy for vascular skin lesions (0.90%). The highest specificity was observed for both bk and ak (0.992% each); however, ak again demonstrated the lowest recall, with a value of 0.01%.

A previous study utilizing a model of binary classification to distinguish between mel and benign dermatologic conditions demonstrated poor performance.¹ Additionally, prior studies have employed a less-strict, open-ended style question approach to examine ChatGPT’s ability to diagnose mel with limited efficacy.⁷ The HAM10000 dataset was specifically selected despite its limitations (including the absence of clinical images and limited diversity in skin tones) due to its comprehensive nature, robust annotation standards, and widespread acceptance in dermatologic AI research. Compared to the Diverse Dermatology Images dataset, which notably lacks skin tone diversity, HAM10000 provides a balanced representation of several dermatologic conditions crucial for multiclass classification tasks, making it suitable for benchmarking AI performance. This study aimed to eliminate these limitations by employing a multiclass classification approach; however, despite this switch, our results indicate continued and major limitations of the diagnostic capabilities of GPT-4o.

In its current form, GPT-4o appeared to demonstrate a clear accuracy bias toward correctly identifying specific and severe dermatologic conditions (eg, mel, bcc) but showed low and variable class-level performance for other categories (eg, ak, nv, df, vsl), with frequent misclassification into melanoma or basal cell carcinoma and low recall for some classes (eTables 1 and 2). This finding emphasized that GPT-4o currently lacks the reliability needed for real-life clinical applications in dermatology, as both binary and multiclass models fail to achieve consistent accurate performance across all skin conditions. Notably, GPT-4o may generate false-positive malignant classifications among patients due to its skew in predicted labels toward labeling benign lesions as malignant.

From the patient perspective, younger individuals may upload images of benign nevi only to unnecessarily fear a mel diagnosis after receiving GPT-4o results. Statistically, younger patients are less likely than older patients to have malignant lesions and more likely to instead present with common vsl or df—lesions that GPT-4o appears likely to identify correctly.⁸ For older users, however, the situation may differ. Beyond ak being misclassified as bcc, older patients also may encounter GPT-4o outputs that mislabel lesions as mel, raising concerns and heightening anxiety. Given the technology’s tendency to overestimate the risk of serious dermatologic conditions, this behavior poses a considerable challenge in its current state and may inadvertently intensify public anxiety around mel.

A notable limitation of our study was that, compared to publicly available datasets, the HAM10000 dataset includes only dermatoscopic images rather than a combination of clinical and dermatoscopic images. Furthermore, the HAM10000 dataset comprises images primarily from White patients, whereas other diverse databases (eg, the Diverse Dermatology Images dataset) may be more suitable for training AI algorithms to accurately diagnose skin lesions in individuals with a variety of skin tones.⁹

Ultimately, our results signal that major advancements in the design and training of LLMs such as GPT-4o are necessary before these systems can be integrated into dermatologic diagnostic decision-making to offer benefit rather than cause harm. Consulting a health care professional rather than relying solely on AI, which might otherwise lead to avoidable stress, unnecessary alarm, and potentially increased health care costs due to unwarranted follow-up and testing, should remain the recommended standard of care for patients suspecting a skin lesion.

To the Editor:

The widespread availability and popularity of ChatGPT (OpenAI) have sparked interest in its potential applications within various fields, including medical diagnostics.¹ In dermatology, large language models (LLMs) already are being cited as a possible way to reliably respond to common patient queries and produce concise patient education materials.^2,3 That being said, there is skepticism regarding the technology’s efficacy and reliability in producing accurate treatment plans, with variability among popular LLMs; for example, a recent study by Chau et al⁴ demonstrated that ChatGPT was best at providing specific and accurate information regarding patient-facing responses to questions about 5 dermatologic diagnoses compared to Google Bard (now rebranded as Google Gemini) and Bing AI (now rebranded as Microsoft Copilot), which more often produced inaccurate or nonspecific responses. Google Bard also declined to answer one prompt.⁴ Large language models also have been evaluated in diagnosing skin lesions. In 2024, SkinGPT-4 (a pretrained multimodel LLM developed by Zhou et al⁵) achieved just over 80% accuracy in interpreting images of skin lesions and was considered informative by 82.5% of board-certified dermatologists, demonstrating that LLMs may have the potential to become integrated into clinical practice.⁵

Our study aimed to evaluate the performance of GPT-4o (OpenAI)—a widely accessible, low-cost LLM—in diagnosing dermatologic conditions using the HAM10000 dataset, a well-curated collection of dermatoscopic images developed for training and benchmarking artificial intelligence (AI) algorithms.⁶ HAM10000 comprises images representing 7 distinct skin conditions: actinic keratoses (ak), basal cell carcinoma (bcc), benign keratosis (bk), dermatofibroma (df), melanoma (mel), melanocytic nevi (nv), and vascular skin lesions (vsl), providing a robust platform for multiclass classification assessment. We evaluated GPT-4o using 100 dermatoscopic images per condition to assess diagnostic accuracy, potential biases, and limitations in skin lesion identification. The HAM10000 dataset was selected because it offers a large standardized reference set of dermatoscopic (rather than conventional clinical) images commonly used in dermatologic AI research. GPT-4o was chosen due to its patient-friendly interface, widespread use, and prior reports suggesting greater reliability in skin lesion assessment compared with other LLMs.

One hundred images from each of the 7 dermatologic categories were randomly selected for use in our analysis in 2024. The images were selected by our data scientist (J.C.) through random sampling from the dataset. Each image was separately presented to GPT-4o without any preprocessing or modification alongside 2 prompts designed to evaluate the diagnostic capabilities of GPT-4o. Both prompts included the same list of 7 dermatologic conditions for answer choices but differed in contextual information, where prompt 1 provided patient demographic information and localization of the dermatological condition but prompt 2 did not provide these details (Table). No follow-up questions were presented.

For prompt 1, the confusion matrix showed a strong bias toward detecting mel and bcc, with high true positives (mel, 83%; bcc, 37%)(eFigure 1). This pattern possibly suggests a tendency to favor malignant labels (eg, mel, BCC) when uncertainty is present. Interestingly, df and vsl also had notable true positives (46% and 37%, respectively), which is unexpected for less critical conditions because the model’s correct classifications were uneven across benign lesions. Actinic keratoses and nv showed higher misclassification rates, suggesting the model struggled to distinguish them from other lesions.

As shown in eTable 1, prompt 1 exhibited the highest recall for mel at 0.83 but performed worse in precision (0.242) and specificity (0.567) compared to ak, which had an extremely low recall (0.03) but very high specificity (0.992) and moderate precision score (0.375). The highest precision score was seen with vsl (0.738), which also achieved high scores in specificity (0.982) and accuracy (0.88) and performed moderately well in recall (0.31). All performance metrics are reported as proportions (0-1.0), wherein 1.0 indicates 100.

For prompt 2, the second confusion matrix followed similar trends as prompt 1 but still differed in key areas (eFigure 2). Melanoma detection remained strong (true positives, 95%), while bcc shows slightly fewer true positives (24%). Vascular skin lesions improve in true positives (40%), and df dropped slightly (33%). The model continues to struggle with ak and nv, with notable misclassifications observed across other categories

Similar to prompt 1, prompt 2 achieved its highest recall for mel (0.95%), but demonstrated lower precision (0.223%) and specificity (0.488%) for this class. Prompt 2 also produced the highest accuracy for vascular skin lesions (0.90%). The highest specificity was observed for both bk and ak (0.992% each); however, ak again demonstrated the lowest recall, with a value of 0.01%.

A previous study utilizing a model of binary classification to distinguish between mel and benign dermatologic conditions demonstrated poor performance.¹ Additionally, prior studies have employed a less-strict, open-ended style question approach to examine ChatGPT’s ability to diagnose mel with limited efficacy.⁷ The HAM10000 dataset was specifically selected despite its limitations (including the absence of clinical images and limited diversity in skin tones) due to its comprehensive nature, robust annotation standards, and widespread acceptance in dermatologic AI research. Compared to the Diverse Dermatology Images dataset, which notably lacks skin tone diversity, HAM10000 provides a balanced representation of several dermatologic conditions crucial for multiclass classification tasks, making it suitable for benchmarking AI performance. This study aimed to eliminate these limitations by employing a multiclass classification approach; however, despite this switch, our results indicate continued and major limitations of the diagnostic capabilities of GPT-4o.

In its current form, GPT-4o appeared to demonstrate a clear accuracy bias toward correctly identifying specific and severe dermatologic conditions (eg, mel, bcc) but showed low and variable class-level performance for other categories (eg, ak, nv, df, vsl), with frequent misclassification into melanoma or basal cell carcinoma and low recall for some classes (eTables 1 and 2). This finding emphasized that GPT-4o currently lacks the reliability needed for real-life clinical applications in dermatology, as both binary and multiclass models fail to achieve consistent accurate performance across all skin conditions. Notably, GPT-4o may generate false-positive malignant classifications among patients due to its skew in predicted labels toward labeling benign lesions as malignant.

From the patient perspective, younger individuals may upload images of benign nevi only to unnecessarily fear a mel diagnosis after receiving GPT-4o results. Statistically, younger patients are less likely than older patients to have malignant lesions and more likely to instead present with common vsl or df—lesions that GPT-4o appears likely to identify correctly.⁸ For older users, however, the situation may differ. Beyond ak being misclassified as bcc, older patients also may encounter GPT-4o outputs that mislabel lesions as mel, raising concerns and heightening anxiety. Given the technology’s tendency to overestimate the risk of serious dermatologic conditions, this behavior poses a considerable challenge in its current state and may inadvertently intensify public anxiety around mel.

A notable limitation of our study was that, compared to publicly available datasets, the HAM10000 dataset includes only dermatoscopic images rather than a combination of clinical and dermatoscopic images. Furthermore, the HAM10000 dataset comprises images primarily from White patients, whereas other diverse databases (eg, the Diverse Dermatology Images dataset) may be more suitable for training AI algorithms to accurately diagnose skin lesions in individuals with a variety of skin tones.⁹

Ultimately, our results signal that major advancements in the design and training of LLMs such as GPT-4o are necessary before these systems can be integrated into dermatologic diagnostic decision-making to offer benefit rather than cause harm. Consulting a health care professional rather than relying solely on AI, which might otherwise lead to avoidable stress, unnecessary alarm, and potentially increased health care costs due to unwarranted follow-up and testing, should remain the recommended standard of care for patients suspecting a skin lesion.

To the Editor:

It is known that dermatologist evaluation of skin conditions in hospitalized patients confers enhanced diagnostic accuracy, timely and appropriate treatment, and an overall reduction in readmissions compared to assessments by nondermatology hospitalists.¹ Dermatology consultations have been shown to alter diagnoses in up to 50% of cases and lead to changes in management in nearly 75% of cases, even for prevalent dermatologic conditions such as drug rashes, cellulitis, and stasis dermatitis.^1,2 Previous studies have observed a multiday reduction in length of hospital stay, a 10-fold reduction in readmission rate, and lower 30-day mortality, all leading to a reduction in patient morbidity and costs to both the patient and the health care system.^3,4 Despite these benefits, there has been a decrease in the number of dermatologists providing inpatient services and a reduction in medical centers offering dermatology consultations over the past several years.⁵ To better appreciate current trends of declining dermatology inpatient and consultative services within our region, we evaluated the availability of dermatology care at hospitals across Virginia.

A simple telephone survey was conducted across community hospitals in Virginia wherein medical staff administrators were asked to provide details regarding their dermatology staffing. The following figures were collected: number of dermatologists on staff, number of dermatologists with consulting privileges, number of affiliated dermatologists, and number of advanced-practice dermatology providers. Follow-up calls were carried out to elaborate on how dermatologists (when available) were integrated into inpatient care workflow and made accessible to hospitalists and emergency medicine departments. Academic centers, military hospitals, and specialty hospitals were excluded from the survey.

To better appreciate the relationships between hospital and population characteristics and the availability of dermatology care, publicly available data were collected on hospital bed counts and regional population density for each facility.^6-9 Spearman rank correlation analyses were conducted in Microsoft Excel to evaluate the association between the number of dermatologists on staff, number of consulting dermatologists, staffed inpatient beds, and population size.

Sixty-four hospitals—more than 70% of the 90 eligible community hospitals—responded to the survey between May and August 2024 and were included in the study. On-staff dermatologists were present at 8 (12.5%) of the hospitals surveyed; of these, 4 (50.0%) hospitals had between 1 and 5 dermatologists, 3 (37.5%) had between 6 and 10 dermatologists, and 1 (12.5%) had between 11 and 15 dermatologists. An additional 4 (6.3%) hospitals provided consultative dermatology services from outside dermatology clinics. Urban hospitals accounted for 9 of 12 (75%) hospitals offering in-house dermatology services, either through on-staff physicians or consultations with clinic-based providers.

Based on Spearman rank correlation analysis, there was a positive correlation between the number of dermatologists on staff and the number of staffed hospital beds (r=0.61; P <.001). Similarly, there was a positive correlation between the number of dermatologists on staff and the population density of the affiliated region (r=0.58; P <.001). Finally, there was a positive correlation between the number of dermatologists on staff and the number of available consulting dermatologists (r=0.89; P <.001).

At facilities with only consultative dermatology services accessible, there often was no formal dermatology team or department present. Rather, the hospitals relied on a loosely affiliated network of dermatology providers or navigated inpatient dermatology needs almost exclusively via internal medicine hospitalists or emergency medicine physicians. When available, dermatology support from dermatology physicians often was provided through teledermatology platforms. Although teledermatology has a large role in increasing access to care within underserved areas, its reliance on images and second-hand case descriptions can limit the provider’s ability to perform a comprehensive examination and assessment. Moreover, it was noted that few hospital representatives could offer clarity on how dermatologists were integrated into the inpatient setting. It remained unclear whether dermatologists were practically accessible to the inpatient care teams in a structured manner.

The uneven distribution and limited availability of dermatology inpatient care in Virginia reflect national trends and underscore ongoing access issues for patients. Without intentional intervention, these trends are expected to continue, contributing to a glaring gap in hospital services as well as to patient morbidity and mortality. The correlation data obtained in our study further qualify these disparities. The positive correlations between dermatologist availability and hospital size and population density suggest that larger, more urban facilities are more likely to offer inpatient dermatology care, whether through staffing or consultation. This relationship is not unexpected, given the greater financial resources and specialist networks available to facilities with large patient volumes. This suggests that dermatology care is shaped by institutional capacity and geographic leverage rather than clinical need, reinforcing existing disparities.

Importantly, it should be noted that the data may overestimate the true availability of dermatologists to these patients. As revealed via follow-up survey calls, respondent facilities that provided dermatology via consultative services often did not have a defined structure for integrating this care into the inpatient workflow. In some instances, dermatologists were technically affiliated with the hospital but had varying levels of practical interaction with the hospital providers and their patients. Administrative staff's differing awareness regarding dermatology interaction with the hospital facility may reveal systemic underutilization and opportunities to improve coordination to achieve the greatest benefit from dermatology services. These observations are further informed by the scope of our study, which focused specifically on community hospitals. The exclusion of academic and military institutions—and the tendency of these to exist in more densely populated areas—may have limited how broadly our findings reflect nationwide dermatology access by omitting more established dermatology departments and specialty care. As a result, regional variations in predominant facility type should be considered when interpreting the implications of these results beyond Virginia’s community hospital system.

In response to access limitations and differences in availability, facilities are turning to integrated teledermatology as a valuable tool to expand the reach of specialist care, particularly in rural or resource-limited settings. This modality acts as an important step toward improving equity in care by beginning to bridge geographic gaps; however, along with these logistical advantages, teledermatology also confers diagnostic limitations and clinical trade-offs that should be thoughtfully considered. Our findings highlight the need to expand access in a way that integrates technological advances with in-person care to build a sustainable and effective path forward without compromising the quality of care patients receive. We present these outcomes to emphasize the importance of increasing dermatology involvement in the care of hospitalized patients, which is a promising strategy to improve patient outcomes and reduce existing disparities in Virginia and nationwide.

To the Editor:

It is known that dermatologist evaluation of skin conditions in hospitalized patients confers enhanced diagnostic accuracy, timely and appropriate treatment, and an overall reduction in readmissions compared to assessments by nondermatology hospitalists.¹ Dermatology consultations have been shown to alter diagnoses in up to 50% of cases and lead to changes in management in nearly 75% of cases, even for prevalent dermatologic conditions such as drug rashes, cellulitis, and stasis dermatitis.^1,2 Previous studies have observed a multiday reduction in length of hospital stay, a 10-fold reduction in readmission rate, and lower 30-day mortality, all leading to a reduction in patient morbidity and costs to both the patient and the health care system.^3,4 Despite these benefits, there has been a decrease in the number of dermatologists providing inpatient services and a reduction in medical centers offering dermatology consultations over the past several years.⁵ To better appreciate current trends of declining dermatology inpatient and consultative services within our region, we evaluated the availability of dermatology care at hospitals across Virginia.

A simple telephone survey was conducted across community hospitals in Virginia wherein medical staff administrators were asked to provide details regarding their dermatology staffing. The following figures were collected: number of dermatologists on staff, number of dermatologists with consulting privileges, number of affiliated dermatologists, and number of advanced-practice dermatology providers. Follow-up calls were carried out to elaborate on how dermatologists (when available) were integrated into inpatient care workflow and made accessible to hospitalists and emergency medicine departments. Academic centers, military hospitals, and specialty hospitals were excluded from the survey.

To better appreciate the relationships between hospital and population characteristics and the availability of dermatology care, publicly available data were collected on hospital bed counts and regional population density for each facility.^6-9 Spearman rank correlation analyses were conducted in Microsoft Excel to evaluate the association between the number of dermatologists on staff, number of consulting dermatologists, staffed inpatient beds, and population size.

Sixty-four hospitals—more than 70% of the 90 eligible community hospitals—responded to the survey between May and August 2024 and were included in the study. On-staff dermatologists were present at 8 (12.5%) of the hospitals surveyed; of these, 4 (50.0%) hospitals had between 1 and 5 dermatologists, 3 (37.5%) had between 6 and 10 dermatologists, and 1 (12.5%) had between 11 and 15 dermatologists. An additional 4 (6.3%) hospitals provided consultative dermatology services from outside dermatology clinics. Urban hospitals accounted for 9 of 12 (75%) hospitals offering in-house dermatology services, either through on-staff physicians or consultations with clinic-based providers.

Based on Spearman rank correlation analysis, there was a positive correlation between the number of dermatologists on staff and the number of staffed hospital beds (r=0.61; P <.001). Similarly, there was a positive correlation between the number of dermatologists on staff and the population density of the affiliated region (r=0.58; P <.001). Finally, there was a positive correlation between the number of dermatologists on staff and the number of available consulting dermatologists (r=0.89; P <.001).

At facilities with only consultative dermatology services accessible, there often was no formal dermatology team or department present. Rather, the hospitals relied on a loosely affiliated network of dermatology providers or navigated inpatient dermatology needs almost exclusively via internal medicine hospitalists or emergency medicine physicians. When available, dermatology support from dermatology physicians often was provided through teledermatology platforms. Although teledermatology has a large role in increasing access to care within underserved areas, its reliance on images and second-hand case descriptions can limit the provider’s ability to perform a comprehensive examination and assessment. Moreover, it was noted that few hospital representatives could offer clarity on how dermatologists were integrated into the inpatient setting. It remained unclear whether dermatologists were practically accessible to the inpatient care teams in a structured manner.

The uneven distribution and limited availability of dermatology inpatient care in Virginia reflect national trends and underscore ongoing access issues for patients. Without intentional intervention, these trends are expected to continue, contributing to a glaring gap in hospital services as well as to patient morbidity and mortality. The correlation data obtained in our study further qualify these disparities. The positive correlations between dermatologist availability and hospital size and population density suggest that larger, more urban facilities are more likely to offer inpatient dermatology care, whether through staffing or consultation. This relationship is not unexpected, given the greater financial resources and specialist networks available to facilities with large patient volumes. This suggests that dermatology care is shaped by institutional capacity and geographic leverage rather than clinical need, reinforcing existing disparities.

Importantly, it should be noted that the data may overestimate the true availability of dermatologists to these patients. As revealed via follow-up survey calls, respondent facilities that provided dermatology via consultative services often did not have a defined structure for integrating this care into the inpatient workflow. In some instances, dermatologists were technically affiliated with the hospital but had varying levels of practical interaction with the hospital providers and their patients. Administrative staff's differing awareness regarding dermatology interaction with the hospital facility may reveal systemic underutilization and opportunities to improve coordination to achieve the greatest benefit from dermatology services. These observations are further informed by the scope of our study, which focused specifically on community hospitals. The exclusion of academic and military institutions—and the tendency of these to exist in more densely populated areas—may have limited how broadly our findings reflect nationwide dermatology access by omitting more established dermatology departments and specialty care. As a result, regional variations in predominant facility type should be considered when interpreting the implications of these results beyond Virginia’s community hospital system.

In response to access limitations and differences in availability, facilities are turning to integrated teledermatology as a valuable tool to expand the reach of specialist care, particularly in rural or resource-limited settings. This modality acts as an important step toward improving equity in care by beginning to bridge geographic gaps; however, along with these logistical advantages, teledermatology also confers diagnostic limitations and clinical trade-offs that should be thoughtfully considered. Our findings highlight the need to expand access in a way that integrates technological advances with in-person care to build a sustainable and effective path forward without compromising the quality of care patients receive. We present these outcomes to emphasize the importance of increasing dermatology involvement in the care of hospitalized patients, which is a promising strategy to improve patient outcomes and reduce existing disparities in Virginia and nationwide.

To the Editor:

It is known that dermatologist evaluation of skin conditions in hospitalized patients confers enhanced diagnostic accuracy, timely and appropriate treatment, and an overall reduction in readmissions compared to assessments by nondermatology hospitalists.¹ Dermatology consultations have been shown to alter diagnoses in up to 50% of cases and lead to changes in management in nearly 75% of cases, even for prevalent dermatologic conditions such as drug rashes, cellulitis, and stasis dermatitis.^1,2 Previous studies have observed a multiday reduction in length of hospital stay, a 10-fold reduction in readmission rate, and lower 30-day mortality, all leading to a reduction in patient morbidity and costs to both the patient and the health care system.^3,4 Despite these benefits, there has been a decrease in the number of dermatologists providing inpatient services and a reduction in medical centers offering dermatology consultations over the past several years.⁵ To better appreciate current trends of declining dermatology inpatient and consultative services within our region, we evaluated the availability of dermatology care at hospitals across Virginia.

A simple telephone survey was conducted across community hospitals in Virginia wherein medical staff administrators were asked to provide details regarding their dermatology staffing. The following figures were collected: number of dermatologists on staff, number of dermatologists with consulting privileges, number of affiliated dermatologists, and number of advanced-practice dermatology providers. Follow-up calls were carried out to elaborate on how dermatologists (when available) were integrated into inpatient care workflow and made accessible to hospitalists and emergency medicine departments. Academic centers, military hospitals, and specialty hospitals were excluded from the survey.

To better appreciate the relationships between hospital and population characteristics and the availability of dermatology care, publicly available data were collected on hospital bed counts and regional population density for each facility.^6-9 Spearman rank correlation analyses were conducted in Microsoft Excel to evaluate the association between the number of dermatologists on staff, number of consulting dermatologists, staffed inpatient beds, and population size.

Sixty-four hospitals—more than 70% of the 90 eligible community hospitals—responded to the survey between May and August 2024 and were included in the study. On-staff dermatologists were present at 8 (12.5%) of the hospitals surveyed; of these, 4 (50.0%) hospitals had between 1 and 5 dermatologists, 3 (37.5%) had between 6 and 10 dermatologists, and 1 (12.5%) had between 11 and 15 dermatologists. An additional 4 (6.3%) hospitals provided consultative dermatology services from outside dermatology clinics. Urban hospitals accounted for 9 of 12 (75%) hospitals offering in-house dermatology services, either through on-staff physicians or consultations with clinic-based providers.

Based on Spearman rank correlation analysis, there was a positive correlation between the number of dermatologists on staff and the number of staffed hospital beds (r=0.61; P <.001). Similarly, there was a positive correlation between the number of dermatologists on staff and the population density of the affiliated region (r=0.58; P <.001). Finally, there was a positive correlation between the number of dermatologists on staff and the number of available consulting dermatologists (r=0.89; P <.001).

At facilities with only consultative dermatology services accessible, there often was no formal dermatology team or department present. Rather, the hospitals relied on a loosely affiliated network of dermatology providers or navigated inpatient dermatology needs almost exclusively via internal medicine hospitalists or emergency medicine physicians. When available, dermatology support from dermatology physicians often was provided through teledermatology platforms. Although teledermatology has a large role in increasing access to care within underserved areas, its reliance on images and second-hand case descriptions can limit the provider’s ability to perform a comprehensive examination and assessment. Moreover, it was noted that few hospital representatives could offer clarity on how dermatologists were integrated into the inpatient setting. It remained unclear whether dermatologists were practically accessible to the inpatient care teams in a structured manner.

The uneven distribution and limited availability of dermatology inpatient care in Virginia reflect national trends and underscore ongoing access issues for patients. Without intentional intervention, these trends are expected to continue, contributing to a glaring gap in hospital services as well as to patient morbidity and mortality. The correlation data obtained in our study further qualify these disparities. The positive correlations between dermatologist availability and hospital size and population density suggest that larger, more urban facilities are more likely to offer inpatient dermatology care, whether through staffing or consultation. This relationship is not unexpected, given the greater financial resources and specialist networks available to facilities with large patient volumes. This suggests that dermatology care is shaped by institutional capacity and geographic leverage rather than clinical need, reinforcing existing disparities.

Importantly, it should be noted that the data may overestimate the true availability of dermatologists to these patients. As revealed via follow-up survey calls, respondent facilities that provided dermatology via consultative services often did not have a defined structure for integrating this care into the inpatient workflow. In some instances, dermatologists were technically affiliated with the hospital but had varying levels of practical interaction with the hospital providers and their patients. Administrative staff's differing awareness regarding dermatology interaction with the hospital facility may reveal systemic underutilization and opportunities to improve coordination to achieve the greatest benefit from dermatology services. These observations are further informed by the scope of our study, which focused specifically on community hospitals. The exclusion of academic and military institutions—and the tendency of these to exist in more densely populated areas—may have limited how broadly our findings reflect nationwide dermatology access by omitting more established dermatology departments and specialty care. As a result, regional variations in predominant facility type should be considered when interpreting the implications of these results beyond Virginia’s community hospital system.

In response to access limitations and differences in availability, facilities are turning to integrated teledermatology as a valuable tool to expand the reach of specialist care, particularly in rural or resource-limited settings. This modality acts as an important step toward improving equity in care by beginning to bridge geographic gaps; however, along with these logistical advantages, teledermatology also confers diagnostic limitations and clinical trade-offs that should be thoughtfully considered. Our findings highlight the need to expand access in a way that integrates technological advances with in-person care to build a sustainable and effective path forward without compromising the quality of care patients receive. We present these outcomes to emphasize the importance of increasing dermatology involvement in the care of hospitalized patients, which is a promising strategy to improve patient outcomes and reduce existing disparities in Virginia and nationwide.

Squamous cell carcinoma (SCC) is the malignant proliferation of keratinocytes in the epidermis of the skin. Most SCCs are caused by UV light exposure, with sex and increased age acting as the primary known risk factors: SCCs are nearly twice as prevalent in men vs women, and the average age of presentation is the middle of the seventh decade of life.¹ In the United States, there are an estimated 1.8 million new SCC cases annually.² Although not usually life threatening, if left untreated, SCC can metastasize, thereby reducing the 10-year survival rate from above 90% with treatment to 16%.^3-6

Most invasive SCC lesions are treated surgically, but intralesional methotrexate (IL-MTX) has emerged as an alternative treatment for cutaneous SCC. It offers the potential for lower-cost, efficacious outpatient treatment.^7-12 Methotrexate competitively inhibits the enzyme dihydrofolate reductase, which converts dihydrofolate into tetrahydrofolate.¹³ In doing so, MTX indirectly prevents the synthesis of thymine, a nucleotide required for DNA synthesis. Thus, MTX can halt DNA synthesis and consequently, cell division. Intralesional MTX has been shown to successfully treat keratoacanthomas, lymphomas, and various inflammatory dermatologic conditions.^8-12 

Surgical options include standard excision, Mohs micrographic surgery, or electrodesiccation and curettage. Surgical treatment has high (92% to 99%) cure rates and typically requires only 1 or 2 appointments.^14,15 Although costs can vary, one 2012 study using Medicare fee schedules found that total costs (including primary procedure, biopsy, follow-up appointments through 2 months, and other associated costs) for cutaneous SCC were $475 for electrodesiccation and curettage, $1302.92 for excision, and $2093.14 for Mohs micrographic surgery.¹⁶ For some patients, surgery is not an ideal option due to the tumor location, poor wound healing, anticoagulation, and cost. In these patients, photodynamic therapy, topical therapy with 5-fluorouracil or imiquimod, radiation, and cryotherapy are options listed in the American Academy of Dermatology guidelines.¹⁵ Compared with surgery, radiation is more demanding on the patient, often requiring multiple visits a week and including common undesirable adverse effects such as radiation dermatitis and prolonged wounds on the lower legs.¹⁷ Radiation also can be costly, with one study reporting costs between $2559 and $3431 for SCC of the forearm.¹⁸ Furthermore, in young patients, radiotherapy can increase the risk for developing nonmelanoma skin cancer later in life.¹⁶ 

Intralesional MTX is a localized treatment option that avoids the high costs of surgery, the side effects of radiotherapy, prolonged healing, and the systemic effects of chemotherapy. Treatment with IL-MTX can vary depending on the number of treatments necessary but usually only costs a few hundred dollars, rarely costing more than $1000.⁷ Although IL-MTX is less expensive, it typically requires several follow-up visits, whereas surgical removal may only require 1 visit.

Prior research has noted the efficacy of IL-MTX as a neoadjuvant therapy, with one study finding that IL-MTX can reduce the size of SCC lesions by an average of 0.52 cm² prior to surgery.¹⁹ Several case studies also have documented the effectiveness of IL-MTX as a treatment for SCC.^20-22 However, larger studies involving multiple patients to evaluate the efficacy of IL-MTX as a sole treatment for SCC are lacking. Gualdi et al²³ looked at the outcomes (complete resolution, partial response, or no response) for SCC treated with IL-MTX and found that 62% (13/21) of patients experienced improvement, with 48% (10/21) experiencing at least 50% improvement. Although these results are promising, further research is needed.

Our study sought to examine IL-MTX efficacy as well as evaluate the dosage and number of appointments/­sessions needed to achieve resolution of the lesions.

Methods

We conducted a retrospective chart review of patients who received only IL-MTX for clinically evident or biopsy-proven SCC at US Dermatology Partners clinics in Phoenix, Arizona, from January 1, 2022, to June 30, 2023. Patients aged 18 to 89 years were included, and they had not received other treatment for their SCC lesions such as radiation or systemic chemotherapy. Each patient received at least 1 dose of IL-MTX, beginning with a concentration of 12.5 mg/mL and with all subsequent doses at a concentration of 25 mg/mL (low dose vs high dose). Lesion resolution was categorized as no gross clinical tumor on follow-up. Patients received additional doses of IL-MTX based on the clinical appearance of their lesion(s).

Patient-level descriptive statistics are reported as mean (SD) or median (interquartile range [IQR]) for continuous variables as well as frequency and percentage for categorical variables. To account for the correlation of multiple lesions within individual patients, marginal Cox proportional hazard models were used. Time as well as cumulative dose to lesion resolution were evaluated and presented via the cumulative hazard function, while differences in resolution were estimated using separate Cox models for age, sex, and initial dose.

Results

In total, 107 different lesions from 21 patients were included in the analysis. The median number of lesions was 4 per patient (range, 1-15; IQR, 2-7), with a mean (SD) age of 80 (6) years. Patients were primarily female (81% [17/21]). From the data provided, the majority of lesions (83% [89/107]) resolved with IL-MTX. Of the 18 unresolved lesions, 5 (5%) were referred for a different procedure, and the remaining 13 (12%) were censored (lost to follow-up). Figure 1 provides the cumulative incidence function for lesion resolution. Approximately 50% of patient lesions resolved by the second appointment. Similarly, Figure 2 provides the cumulative dose function for lesion resolution; the median cumulative total dose for resolution was 5 mg (IQR, 2.5–12.5). Finally, concerning the ratio for case resolution, no difference in hazard ratio (HR) was observed for age (female vs male, HR: 1.01; 95% CI: 0.96-1.06), biological sex (HR, 1.01; 95% CI, 0.63-1.63), or initial dose (high vs low, HR: 1.13; 95% CI: 0.77-1.65).

Comment

Results of this study demonstrate the efficacy of IL-MTX for the treatment of cutaneous SCC. More than 80% of the lesions resolved by IL-MTX alone. This treatment approach is more cost-effective with fewer adverse effects when compared to other options. In our study, treatment with IL-MTX also proved to be reasonable in terms of the number of appointments and total dose required, with more than 50% of lesions resolving within 2 appointments and a median cumulative total dose of 5 mg. Intralesional MTX appears to be similarly efficacious in men and women, and the concentration of the initial dose (12.5 mg/mL vs 25 mg/mL) does not change the treatment outcome.

Although these data are encouraging for the use of IL-MTX in the treatment of SCC, future work should consider the relationships between lesion characteristics (such as size and location) and case resolution with IL-MTX as well as recurrence rates with lesions treated by IL-MTX compared to other treatment options.

Conclusion

This study demonstrated the efficacy of IL-MTX as a treatment for SCC that is cost-effective, avoids bothersome side effects, and can be accomplished in relatively few appointments. However, more data are needed to characterize the lesion type best suited to this treatment.

Squamous cell carcinoma (SCC) is the malignant proliferation of keratinocytes in the epidermis of the skin. Most SCCs are caused by UV light exposure, with sex and increased age acting as the primary known risk factors: SCCs are nearly twice as prevalent in men vs women, and the average age of presentation is the middle of the seventh decade of life.¹ In the United States, there are an estimated 1.8 million new SCC cases annually.² Although not usually life threatening, if left untreated, SCC can metastasize, thereby reducing the 10-year survival rate from above 90% with treatment to 16%.^3-6

Most invasive SCC lesions are treated surgically, but intralesional methotrexate (IL-MTX) has emerged as an alternative treatment for cutaneous SCC. It offers the potential for lower-cost, efficacious outpatient treatment.^7-12 Methotrexate competitively inhibits the enzyme dihydrofolate reductase, which converts dihydrofolate into tetrahydrofolate.¹³ In doing so, MTX indirectly prevents the synthesis of thymine, a nucleotide required for DNA synthesis. Thus, MTX can halt DNA synthesis and consequently, cell division. Intralesional MTX has been shown to successfully treat keratoacanthomas, lymphomas, and various inflammatory dermatologic conditions.^8-12 

Surgical options include standard excision, Mohs micrographic surgery, or electrodesiccation and curettage. Surgical treatment has high (92% to 99%) cure rates and typically requires only 1 or 2 appointments.^14,15 Although costs can vary, one 2012 study using Medicare fee schedules found that total costs (including primary procedure, biopsy, follow-up appointments through 2 months, and other associated costs) for cutaneous SCC were $475 for electrodesiccation and curettage, $1302.92 for excision, and $2093.14 for Mohs micrographic surgery.¹⁶ For some patients, surgery is not an ideal option due to the tumor location, poor wound healing, anticoagulation, and cost. In these patients, photodynamic therapy, topical therapy with 5-fluorouracil or imiquimod, radiation, and cryotherapy are options listed in the American Academy of Dermatology guidelines.¹⁵ Compared with surgery, radiation is more demanding on the patient, often requiring multiple visits a week and including common undesirable adverse effects such as radiation dermatitis and prolonged wounds on the lower legs.¹⁷ Radiation also can be costly, with one study reporting costs between $2559 and $3431 for SCC of the forearm.¹⁸ Furthermore, in young patients, radiotherapy can increase the risk for developing nonmelanoma skin cancer later in life.¹⁶ 

Intralesional MTX is a localized treatment option that avoids the high costs of surgery, the side effects of radiotherapy, prolonged healing, and the systemic effects of chemotherapy. Treatment with IL-MTX can vary depending on the number of treatments necessary but usually only costs a few hundred dollars, rarely costing more than $1000.⁷ Although IL-MTX is less expensive, it typically requires several follow-up visits, whereas surgical removal may only require 1 visit.

Prior research has noted the efficacy of IL-MTX as a neoadjuvant therapy, with one study finding that IL-MTX can reduce the size of SCC lesions by an average of 0.52 cm² prior to surgery.¹⁹ Several case studies also have documented the effectiveness of IL-MTX as a treatment for SCC.^20-22 However, larger studies involving multiple patients to evaluate the efficacy of IL-MTX as a sole treatment for SCC are lacking. Gualdi et al²³ looked at the outcomes (complete resolution, partial response, or no response) for SCC treated with IL-MTX and found that 62% (13/21) of patients experienced improvement, with 48% (10/21) experiencing at least 50% improvement. Although these results are promising, further research is needed.

Our study sought to examine IL-MTX efficacy as well as evaluate the dosage and number of appointments/­sessions needed to achieve resolution of the lesions.

Methods

We conducted a retrospective chart review of patients who received only IL-MTX for clinically evident or biopsy-proven SCC at US Dermatology Partners clinics in Phoenix, Arizona, from January 1, 2022, to June 30, 2023. Patients aged 18 to 89 years were included, and they had not received other treatment for their SCC lesions such as radiation or systemic chemotherapy. Each patient received at least 1 dose of IL-MTX, beginning with a concentration of 12.5 mg/mL and with all subsequent doses at a concentration of 25 mg/mL (low dose vs high dose). Lesion resolution was categorized as no gross clinical tumor on follow-up. Patients received additional doses of IL-MTX based on the clinical appearance of their lesion(s).

Patient-level descriptive statistics are reported as mean (SD) or median (interquartile range [IQR]) for continuous variables as well as frequency and percentage for categorical variables. To account for the correlation of multiple lesions within individual patients, marginal Cox proportional hazard models were used. Time as well as cumulative dose to lesion resolution were evaluated and presented via the cumulative hazard function, while differences in resolution were estimated using separate Cox models for age, sex, and initial dose.

Results

In total, 107 different lesions from 21 patients were included in the analysis. The median number of lesions was 4 per patient (range, 1-15; IQR, 2-7), with a mean (SD) age of 80 (6) years. Patients were primarily female (81% [17/21]). From the data provided, the majority of lesions (83% [89/107]) resolved with IL-MTX. Of the 18 unresolved lesions, 5 (5%) were referred for a different procedure, and the remaining 13 (12%) were censored (lost to follow-up). Figure 1 provides the cumulative incidence function for lesion resolution. Approximately 50% of patient lesions resolved by the second appointment. Similarly, Figure 2 provides the cumulative dose function for lesion resolution; the median cumulative total dose for resolution was 5 mg (IQR, 2.5–12.5). Finally, concerning the ratio for case resolution, no difference in hazard ratio (HR) was observed for age (female vs male, HR: 1.01; 95% CI: 0.96-1.06), biological sex (HR, 1.01; 95% CI, 0.63-1.63), or initial dose (high vs low, HR: 1.13; 95% CI: 0.77-1.65).

Comment

Results of this study demonstrate the efficacy of IL-MTX for the treatment of cutaneous SCC. More than 80% of the lesions resolved by IL-MTX alone. This treatment approach is more cost-effective with fewer adverse effects when compared to other options. In our study, treatment with IL-MTX also proved to be reasonable in terms of the number of appointments and total dose required, with more than 50% of lesions resolving within 2 appointments and a median cumulative total dose of 5 mg. Intralesional MTX appears to be similarly efficacious in men and women, and the concentration of the initial dose (12.5 mg/mL vs 25 mg/mL) does not change the treatment outcome.

Although these data are encouraging for the use of IL-MTX in the treatment of SCC, future work should consider the relationships between lesion characteristics (such as size and location) and case resolution with IL-MTX as well as recurrence rates with lesions treated by IL-MTX compared to other treatment options.

Conclusion

This study demonstrated the efficacy of IL-MTX as a treatment for SCC that is cost-effective, avoids bothersome side effects, and can be accomplished in relatively few appointments. However, more data are needed to characterize the lesion type best suited to this treatment.

Squamous cell carcinoma (SCC) is the malignant proliferation of keratinocytes in the epidermis of the skin. Most SCCs are caused by UV light exposure, with sex and increased age acting as the primary known risk factors: SCCs are nearly twice as prevalent in men vs women, and the average age of presentation is the middle of the seventh decade of life.¹ In the United States, there are an estimated 1.8 million new SCC cases annually.² Although not usually life threatening, if left untreated, SCC can metastasize, thereby reducing the 10-year survival rate from above 90% with treatment to 16%.^3-6

Most invasive SCC lesions are treated surgically, but intralesional methotrexate (IL-MTX) has emerged as an alternative treatment for cutaneous SCC. It offers the potential for lower-cost, efficacious outpatient treatment.^7-12 Methotrexate competitively inhibits the enzyme dihydrofolate reductase, which converts dihydrofolate into tetrahydrofolate.¹³ In doing so, MTX indirectly prevents the synthesis of thymine, a nucleotide required for DNA synthesis. Thus, MTX can halt DNA synthesis and consequently, cell division. Intralesional MTX has been shown to successfully treat keratoacanthomas, lymphomas, and various inflammatory dermatologic conditions.^8-12 

Surgical options include standard excision, Mohs micrographic surgery, or electrodesiccation and curettage. Surgical treatment has high (92% to 99%) cure rates and typically requires only 1 or 2 appointments.^14,15 Although costs can vary, one 2012 study using Medicare fee schedules found that total costs (including primary procedure, biopsy, follow-up appointments through 2 months, and other associated costs) for cutaneous SCC were $475 for electrodesiccation and curettage, $1302.92 for excision, and $2093.14 for Mohs micrographic surgery.¹⁶ For some patients, surgery is not an ideal option due to the tumor location, poor wound healing, anticoagulation, and cost. In these patients, photodynamic therapy, topical therapy with 5-fluorouracil or imiquimod, radiation, and cryotherapy are options listed in the American Academy of Dermatology guidelines.¹⁵ Compared with surgery, radiation is more demanding on the patient, often requiring multiple visits a week and including common undesirable adverse effects such as radiation dermatitis and prolonged wounds on the lower legs.¹⁷ Radiation also can be costly, with one study reporting costs between $2559 and $3431 for SCC of the forearm.¹⁸ Furthermore, in young patients, radiotherapy can increase the risk for developing nonmelanoma skin cancer later in life.¹⁶ 

Intralesional MTX is a localized treatment option that avoids the high costs of surgery, the side effects of radiotherapy, prolonged healing, and the systemic effects of chemotherapy. Treatment with IL-MTX can vary depending on the number of treatments necessary but usually only costs a few hundred dollars, rarely costing more than $1000.⁷ Although IL-MTX is less expensive, it typically requires several follow-up visits, whereas surgical removal may only require 1 visit.

Prior research has noted the efficacy of IL-MTX as a neoadjuvant therapy, with one study finding that IL-MTX can reduce the size of SCC lesions by an average of 0.52 cm² prior to surgery.¹⁹ Several case studies also have documented the effectiveness of IL-MTX as a treatment for SCC.^20-22 However, larger studies involving multiple patients to evaluate the efficacy of IL-MTX as a sole treatment for SCC are lacking. Gualdi et al²³ looked at the outcomes (complete resolution, partial response, or no response) for SCC treated with IL-MTX and found that 62% (13/21) of patients experienced improvement, with 48% (10/21) experiencing at least 50% improvement. Although these results are promising, further research is needed.

Our study sought to examine IL-MTX efficacy as well as evaluate the dosage and number of appointments/­sessions needed to achieve resolution of the lesions.

Methods

We conducted a retrospective chart review of patients who received only IL-MTX for clinically evident or biopsy-proven SCC at US Dermatology Partners clinics in Phoenix, Arizona, from January 1, 2022, to June 30, 2023. Patients aged 18 to 89 years were included, and they had not received other treatment for their SCC lesions such as radiation or systemic chemotherapy. Each patient received at least 1 dose of IL-MTX, beginning with a concentration of 12.5 mg/mL and with all subsequent doses at a concentration of 25 mg/mL (low dose vs high dose). Lesion resolution was categorized as no gross clinical tumor on follow-up. Patients received additional doses of IL-MTX based on the clinical appearance of their lesion(s).

Patient-level descriptive statistics are reported as mean (SD) or median (interquartile range [IQR]) for continuous variables as well as frequency and percentage for categorical variables. To account for the correlation of multiple lesions within individual patients, marginal Cox proportional hazard models were used. Time as well as cumulative dose to lesion resolution were evaluated and presented via the cumulative hazard function, while differences in resolution were estimated using separate Cox models for age, sex, and initial dose.

Results

In total, 107 different lesions from 21 patients were included in the analysis. The median number of lesions was 4 per patient (range, 1-15; IQR, 2-7), with a mean (SD) age of 80 (6) years. Patients were primarily female (81% [17/21]). From the data provided, the majority of lesions (83% [89/107]) resolved with IL-MTX. Of the 18 unresolved lesions, 5 (5%) were referred for a different procedure, and the remaining 13 (12%) were censored (lost to follow-up). Figure 1 provides the cumulative incidence function for lesion resolution. Approximately 50% of patient lesions resolved by the second appointment. Similarly, Figure 2 provides the cumulative dose function for lesion resolution; the median cumulative total dose for resolution was 5 mg (IQR, 2.5–12.5). Finally, concerning the ratio for case resolution, no difference in hazard ratio (HR) was observed for age (female vs male, HR: 1.01; 95% CI: 0.96-1.06), biological sex (HR, 1.01; 95% CI, 0.63-1.63), or initial dose (high vs low, HR: 1.13; 95% CI: 0.77-1.65).

Comment

Results of this study demonstrate the efficacy of IL-MTX for the treatment of cutaneous SCC. More than 80% of the lesions resolved by IL-MTX alone. This treatment approach is more cost-effective with fewer adverse effects when compared to other options. In our study, treatment with IL-MTX also proved to be reasonable in terms of the number of appointments and total dose required, with more than 50% of lesions resolving within 2 appointments and a median cumulative total dose of 5 mg. Intralesional MTX appears to be similarly efficacious in men and women, and the concentration of the initial dose (12.5 mg/mL vs 25 mg/mL) does not change the treatment outcome.

Although these data are encouraging for the use of IL-MTX in the treatment of SCC, future work should consider the relationships between lesion characteristics (such as size and location) and case resolution with IL-MTX as well as recurrence rates with lesions treated by IL-MTX compared to other treatment options.

Conclusion

This study demonstrated the efficacy of IL-MTX as a treatment for SCC that is cost-effective, avoids bothersome side effects, and can be accomplished in relatively few appointments. However, more data are needed to characterize the lesion type best suited to this treatment.

Large epidemiologic studies have shown disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status (SES). Racial and ethnic minorities and individuals of lower SES have experienced disproportionately higher rates of intensive care unit (ICU) admission and death. In Washington, DC, Black individuals (47% of the population) accounted for 51% of COVID-19 cases and 75% of deaths. In comparison, White individuals (41% of the population) accounted for 21% of cases and 11% of deaths.¹ Place of residence, such as living in socially vulnerable communities, has also been shown to be associated with higher rates of COVID-19 mortality and lower vaccination rates.^2-4 Social and structural inequities, such as limited access to health care services and mistrust of the health care system, may explain some of the observed disparities.⁵ However, data are limited regarding COVID-19 outcomes for individuals with equal access to care.

The Veterans Health Administration (VHA) is the largest integrated US health care system and operates 123 acute care hospitals. Previous research has demonstrated that disparities in outcomes for other diseases are attenuated or erased among veterans receiving VHA care.^6,7 Based on literature from the pandemic, markers of health care inequity relating to SES (eg, place of residence, median income) are expected to impact the outcomes of patients acutely hospitalized with COVID-19.⁴ We hypothesized that the impact on clinical outcomes of infection would be mitigated for veterans receiving VHA care.

This retrospective cohort study included veterans who presented to Washington Veterans Affairs Medical Center (WVAMC) with the goal of determining whether place of residence as a marker of SES, health care access, and median income were predictive of COVID-19 disease severity.

Methods

The WVAMC serves about 125,000 veterans across the metropolitan area, including parts of Maryland and Virginia. It is a high-complexity hospital with 164 acute care beds, 30 psychosocial residential rehabilitation beds, and an adjacent 120-bed community living center providing long-term, hospice, and palliative care.⁸

The WVAMC developed a dashboard that tracked patients with COVID-19 through on-site testing by admission date, ward, and other key demographics (PowerBi, Corporate Data Warehouse). All patients admitted to WVAMC with a diagnosis of COVID-19 between March 1, 2020, and June 30, 2021, were included in this retrospective review. Using the Computerized Patient Record System (CPRS) and the dashboard, we collected demographic information, baseline clinical diagnoses, laboratory results, and clinical interventions for all patients with documented COVID-19 infection as established by laboratory testing methods available at the time of diagnosis. Veterans treated exclusively outside the WVAMC were excluded. Hospitalization was defined as any acute inpatient admission or transfer recorded within 5 days before and 30 days after the laboratory collection of a positive COVID-19 test. Home testing kits were not widely available during the study period. An ICU stay was defined as any inpatient admission or transfer recorded within 5 days before or 30 days after the laboratory collection of a positive COVID-19 test for which the ward location had the specialty of medical or surgical ICU. Death due to COVID-19 was defined as occurring within 42 days (6 weeks) of a positive COVID-19 test.⁹ This definition assumed that during the peak of the pandemic, COVID-19 was the attributable cause of death, despite the possible contribution of underlying health conditions.

Patients’ admission periods were based on US Centers for Disease Control and Prevention (CDC) national data and classified as early 2020 (January 2020–April 2020), mid-2020 (May 2020–August 2020), late 2020 (September 2020–December 2020), and early 2021 (January 2021–April 2021).¹⁰ We chose to use these time periods as surrogates for the frequent changes in circulating COVID-19 variants, surges in case numbers, therapies and interventions available during the pandemic. The dominant COVID-19 variant during the study period was Alpha (B.1.17). Beta (B.1.351) variants were circulating infrequently, and Delta and Omicron appeared after the study period.¹¹ Treatment strategies evolved rapidly with emerging evidence, including the use of dexamethasone, beginning in June 2020.¹² WVAMC followed the Advisory Committee on Immunization Practices guidance on vaccination rollout beginning in December 2020.¹³

Patients' income was estimated by the median household income of the zip code residence based on US Census Bureau 2021 estimates and was assessed as both a continuous and categorical variable.¹⁴ The Charlson Comorbidity Index (CCI) was included in models as a continuous variable.¹⁵ Variables contributing to the CCI include myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, hemiplegia or paraplegia, ulcer disease, hepatic disease, diabetes (with or without end-organ damage), chronic obstructive pulmonary disease (COPD), connective tissue disease, leukemia, lymphoma, moderate or severe renal disease, solid tumor (with or without metastases), and HIV/AIDS. The WVAMC Institutional Review Board approved this study (IRB #1573071).

Variables

This study assessed 3 primary outcomes as indicators of disease severity during hospitalization: need for high-flow oxygen (HFO), intubation, and presumed mortality at any time during hospitalization. The following variables were collected as potential social determinants or clinical risk-adjustment predictors of disease severity outcomes: age; sex; race and ethnicity; median income for patient’s zip code residence, state, and county; wards within Washington, DC; comorbidities, CCI; tobacco use; and body mass index.¹⁵ Although medications at baseline, treatments during hospitalization for COVID-19, and laboratory parameters during hospitalization are shown in eAppendices 1 and 2, they are beyond the scope of this analysis.

Statistical Analysis

Three types of logistic regression models were calculated for predicting the disease severity outcomes: (1) simple unadjusted models; (2) models predicting from single variables plus age (age-adjusted); and (3) multivariable models using all nonredundant potential predictors with adequate sample sizes (multivariable). Variables were considered to have inadequate sample sizes if there was nontrivial missing data or small numbers within categories, (eg, AIDS, connective tissue disease). Potential predictors for the multivariable model included age, sex, race, median income by zip code residence, CCI, CDC admission period, obesity, hypertension, chronic kidney disease, obstructive sleep apnea (OSA), diabetes, COPD or asthma, liver disease, antibiotics, and acute kidney injury.

For the multivariable models, the following modifications were made to avoid unreliable parameter estimation and computation problems (quasi-separation): age and CCI were included as continuous rather than categorical variables. Race was recoded as a 2-category variable (Black vs other [White, Hispanic, American Indian, Alaska Native, Asian, Native Hawaiian, and Pacific Islander]), and ethnicity was excluded because of the small number of patients in this group (n = 16). Admission period was included. Predicted probability plots were generated for each outcome with continuous independent predictors (income and CCI), both unadjusted and adjusted for age as a continuous covariate. All analyses were performed using SAS version 9.4.

Heat Maps

Heat maps were generated to visualize the geospatial distribution of COVID-19 cases and median incomes across zip codes in the greater Washington, DC area. Patient case data and median income, aggregated by zip code, were imported using ArcGIS Online. A zip code boundary layer from Esri (United States Zip Code Boundaries) was used to spatially align the case data. Data were joined by matching zip codes or median incomes in the patient dataset to those in the boundary layer. The resulting polygon layer was styled using the Counts and Amounts (Color) symbology in ArcGIS Online, with case counts or median income determining the intensity of the color gradient.

Results

Between March 1, 2020, and June 30, 2021, 348 patients were hospitalized with COVID-19 (Table 1). The mean (SD) age was 68.4 (13.9) years, 313 patients (90.2%) were male, 281 patients (83.4%) were Black, 47 patients (13.6%) were White, and 16 patients (4.8%) were Hispanic. One hundred forty patients (40.2%) resided in Washington, DC, 151 (43.4%) in Maryland, and 19 (5.5%) in Virginia. HFO was received by 86 patients (24.7%), 33 (9.5%) required intubation and mechanical ventilation, and 57 (16.4%) died. All intubations and deaths occurred among patients aged > 50 years, with death occurring in 17.8% of patients aged > 50 years.

Demographic characteristics and baseline comorbidities associated with COVID-19 disease severity can be found in eAppendix 2. In unadjusted analyses, age was significantly associated with the risk of HFO, with a mean (SD) age of 72.5 (11.7) years among those requiring HFO and 67.1 (14.4) years among patients without HFO (odds ratio [OR], 1.03; 95% CI, 1.01-1.05; P = .002). Although age was not associated with the risk of intubation, it was significantly associated with mortality. Patients who died had a mean (SD) age of 76.8 (11.8) years compared with 66.8 (13.7) years among survivors (OR, 1.06; 95% CI, 1.04-1.09; P < .001).

Compared with patients with no comorbidities, CCI categories of mild, moderate, and severe were associated with increased risk of requiring HFO (eAppendix 3). The adjusted OR (aOR) was highest among patients with severe CCI (aOR, 7.00; 95% CI, 2.42-20.32; P = .0007). In age-adjusted analyses, CCI was not associated with intubation or mortality.

Geospatial Analyses

State of residence, county of residence, and geographic area (including Washington, DC wards, and geographic divisions within counties of residence in Maryland and Virginia) were not associated with the clinical outcomes studied (eAppendix 4). However, zip code-based median income, analyzed as a continuous variable, was associated with a reduced likelihood of receiving HFO (aOR, 0.91; 95% CI, 0.84-0.99; P = .03). Income was not significantly associated with intubation or mortality.

The majority of patients hospitalized for COVID-19 at WVAMC resided in zip codes in eastern Washington, DC, inclusive of wards 7 and 8, and Prince George’s County, Maryland (Figure 1). These areas also corresponded to the lowest median household income by zip code (Figure 2).

Multivariable Analysis

Significant predictors of HFO requirement included comorbid diabetes (OR, 2.42; 95% CI, 1.27-4.61; P = .006) and liver disease or cirrhosis (OR, 2.19; 95% CI, 1.09-4.39; P = .02) (Table 2). CDC admission period was also associated with HFO need. Patients admitted after early 2020 had lower odds of receiving HFO. Race and median income based on zip code residence were not associated with HFO requirement.

Comorbid liver disease or cirrhosis was a significant predictor of intubation (OR, 2.81; 95% CI, 1.07-7.40; P = .03). CDC admission period was associated with intubation with lower odds of intubation for patients admitted after early 2020. Race and median income by zip code were not associated with intubation.

Significant predictors of mortality included age (OR, 2.20; 95% CI, 1.55-3.14; P = .0001), comorbid liver disease or cirrhosis (OR, 2.97; 95% CI, 1.31-6.74; P = .008), and OSA (OR, 3.45; 95% CI, 1.49-7.97; P = .003). CDC admission period was associated with mortality, with lower odds of intubation for patients admitted in mid- and late 2020. Race and median income by zip code residence were not associated with intubation.

Discussion

In this study of COVID-19 disease severity at a large integrated health care system that provides equal access to care, race, ethnicity, and geographic location were not associated with the need for HFO, intubation, or presumed mortality. Median income by zip code residence was associated with reduced HFO use in univariable analyses but not in multivariable models.

These findings support existing literature suggesting that race and ethnicity alone do not explain disparities in COVID-19 outcomes. Multiple studies have demonstrated that disparities in health outcomes have been reduced for patients receiving VHA care.^6,16-19 However, even within a health care system with assumed equal access, the finding of an association between income and need for HFO in the univariable analysis may reflect a greater likelihood of delays in care due to structural barriers. Multiple studies suggest low SES may be an independent risk factor for severe COVID-19 disease. Individuals with low SES have higher rates of chronic diseases of obesity, diabetes, heart disease, and lung disease; thus, they are also at greater risk of serious illness with COVID-19.^20-24 Socioeconomic disadvantage may also have limited individuals’ ability to engage in protective behaviors to reduce COVID-19 infection risk, including food stockpiling, social distancing, avoidance of public transportation, and refraining from working in “essential jobs.”²¹

Beyond SES, place of residence also influences health outcomes. Prior literature supports using zip codes to assess area-based SES status and monitor health disparities.²⁵ The Social Vulnerability Index incorporates SES factors for communities and measures social determinates of health at a zip code level exclusive of race and ethnicity.²⁶ Socially vulnerable communities are known to have higher rates of chronic diseases, COVID-19 mortality, and lower vaccination rates.³ Within a defined geographic area, an individual’s outcome for COVID-19 can be influenced by individual resources such as access to care and median income. Disposable income may mitigate COVID-19 risk by facilitating timely care, reducing occupational exposure, improving housing stability, and supporting health-promoting behaviors.²¹

Limitations

Due to the evolving nature of the COVID-19 pandemic, variants, treatments, and interventions varied throughout the study period and are not included in this analysis. In late December 2020, COVID-19 vaccination was approved with a tiered allocation for at-risk patients and direct health care professionals. Three of the 4 study periods analyzed in this study were prior to vaccine rollout and therefore vaccination history was not assessed. However, we tried to capture the evolving changes in COVID-19 variants, treatments and interventions, and skill in treating the disease through use of CDC-defined time frames. Another limitation is that some studies have shown that use of median income by zip code residence can underestimate mortality.²⁷ Also, shared resources and access to other sources of disposable income can impact the immediate attainment of social needs. For example, during the COVID-19 pandemic, health care systems in Washington, DC assisted vulnerable individuals by providing food, housing, and other resources.^28,29 Finally, the modest sample size limits generalizability and power to detect differences for certain variables, including Hispanic ethnicity.

Conclusions

There have been widely described disparities in disease severity and death during the COVID-19 pandemic. In this urban veteran cohort of hospitalized patients, there was no difference in the need for intubation or mortality associated with race. The findings suggest that a lower median income by zip code residence may be associated with greater disease severity at presentation, but do not predict severe outcomes and mortality overall. VHA care, which provides equal access to care, may mitigate the disparities seen in the private sector.

Large epidemiologic studies have shown disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status (SES). Racial and ethnic minorities and individuals of lower SES have experienced disproportionately higher rates of intensive care unit (ICU) admission and death. In Washington, DC, Black individuals (47% of the population) accounted for 51% of COVID-19 cases and 75% of deaths. In comparison, White individuals (41% of the population) accounted for 21% of cases and 11% of deaths.¹ Place of residence, such as living in socially vulnerable communities, has also been shown to be associated with higher rates of COVID-19 mortality and lower vaccination rates.^2-4 Social and structural inequities, such as limited access to health care services and mistrust of the health care system, may explain some of the observed disparities.⁵ However, data are limited regarding COVID-19 outcomes for individuals with equal access to care.

The Veterans Health Administration (VHA) is the largest integrated US health care system and operates 123 acute care hospitals. Previous research has demonstrated that disparities in outcomes for other diseases are attenuated or erased among veterans receiving VHA care.^6,7 Based on literature from the pandemic, markers of health care inequity relating to SES (eg, place of residence, median income) are expected to impact the outcomes of patients acutely hospitalized with COVID-19.⁴ We hypothesized that the impact on clinical outcomes of infection would be mitigated for veterans receiving VHA care.

This retrospective cohort study included veterans who presented to Washington Veterans Affairs Medical Center (WVAMC) with the goal of determining whether place of residence as a marker of SES, health care access, and median income were predictive of COVID-19 disease severity.

Methods

The WVAMC serves about 125,000 veterans across the metropolitan area, including parts of Maryland and Virginia. It is a high-complexity hospital with 164 acute care beds, 30 psychosocial residential rehabilitation beds, and an adjacent 120-bed community living center providing long-term, hospice, and palliative care.⁸

The WVAMC developed a dashboard that tracked patients with COVID-19 through on-site testing by admission date, ward, and other key demographics (PowerBi, Corporate Data Warehouse). All patients admitted to WVAMC with a diagnosis of COVID-19 between March 1, 2020, and June 30, 2021, were included in this retrospective review. Using the Computerized Patient Record System (CPRS) and the dashboard, we collected demographic information, baseline clinical diagnoses, laboratory results, and clinical interventions for all patients with documented COVID-19 infection as established by laboratory testing methods available at the time of diagnosis. Veterans treated exclusively outside the WVAMC were excluded. Hospitalization was defined as any acute inpatient admission or transfer recorded within 5 days before and 30 days after the laboratory collection of a positive COVID-19 test. Home testing kits were not widely available during the study period. An ICU stay was defined as any inpatient admission or transfer recorded within 5 days before or 30 days after the laboratory collection of a positive COVID-19 test for which the ward location had the specialty of medical or surgical ICU. Death due to COVID-19 was defined as occurring within 42 days (6 weeks) of a positive COVID-19 test.⁹ This definition assumed that during the peak of the pandemic, COVID-19 was the attributable cause of death, despite the possible contribution of underlying health conditions.

Patients’ admission periods were based on US Centers for Disease Control and Prevention (CDC) national data and classified as early 2020 (January 2020–April 2020), mid-2020 (May 2020–August 2020), late 2020 (September 2020–December 2020), and early 2021 (January 2021–April 2021).¹⁰ We chose to use these time periods as surrogates for the frequent changes in circulating COVID-19 variants, surges in case numbers, therapies and interventions available during the pandemic. The dominant COVID-19 variant during the study period was Alpha (B.1.17). Beta (B.1.351) variants were circulating infrequently, and Delta and Omicron appeared after the study period.¹¹ Treatment strategies evolved rapidly with emerging evidence, including the use of dexamethasone, beginning in June 2020.¹² WVAMC followed the Advisory Committee on Immunization Practices guidance on vaccination rollout beginning in December 2020.¹³

Patients' income was estimated by the median household income of the zip code residence based on US Census Bureau 2021 estimates and was assessed as both a continuous and categorical variable.¹⁴ The Charlson Comorbidity Index (CCI) was included in models as a continuous variable.¹⁵ Variables contributing to the CCI include myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, hemiplegia or paraplegia, ulcer disease, hepatic disease, diabetes (with or without end-organ damage), chronic obstructive pulmonary disease (COPD), connective tissue disease, leukemia, lymphoma, moderate or severe renal disease, solid tumor (with or without metastases), and HIV/AIDS. The WVAMC Institutional Review Board approved this study (IRB #1573071).

Variables

This study assessed 3 primary outcomes as indicators of disease severity during hospitalization: need for high-flow oxygen (HFO), intubation, and presumed mortality at any time during hospitalization. The following variables were collected as potential social determinants or clinical risk-adjustment predictors of disease severity outcomes: age; sex; race and ethnicity; median income for patient’s zip code residence, state, and county; wards within Washington, DC; comorbidities, CCI; tobacco use; and body mass index.¹⁵ Although medications at baseline, treatments during hospitalization for COVID-19, and laboratory parameters during hospitalization are shown in eAppendices 1 and 2, they are beyond the scope of this analysis.

Statistical Analysis

Three types of logistic regression models were calculated for predicting the disease severity outcomes: (1) simple unadjusted models; (2) models predicting from single variables plus age (age-adjusted); and (3) multivariable models using all nonredundant potential predictors with adequate sample sizes (multivariable). Variables were considered to have inadequate sample sizes if there was nontrivial missing data or small numbers within categories, (eg, AIDS, connective tissue disease). Potential predictors for the multivariable model included age, sex, race, median income by zip code residence, CCI, CDC admission period, obesity, hypertension, chronic kidney disease, obstructive sleep apnea (OSA), diabetes, COPD or asthma, liver disease, antibiotics, and acute kidney injury.

For the multivariable models, the following modifications were made to avoid unreliable parameter estimation and computation problems (quasi-separation): age and CCI were included as continuous rather than categorical variables. Race was recoded as a 2-category variable (Black vs other [White, Hispanic, American Indian, Alaska Native, Asian, Native Hawaiian, and Pacific Islander]), and ethnicity was excluded because of the small number of patients in this group (n = 16). Admission period was included. Predicted probability plots were generated for each outcome with continuous independent predictors (income and CCI), both unadjusted and adjusted for age as a continuous covariate. All analyses were performed using SAS version 9.4.

Heat Maps

Heat maps were generated to visualize the geospatial distribution of COVID-19 cases and median incomes across zip codes in the greater Washington, DC area. Patient case data and median income, aggregated by zip code, were imported using ArcGIS Online. A zip code boundary layer from Esri (United States Zip Code Boundaries) was used to spatially align the case data. Data were joined by matching zip codes or median incomes in the patient dataset to those in the boundary layer. The resulting polygon layer was styled using the Counts and Amounts (Color) symbology in ArcGIS Online, with case counts or median income determining the intensity of the color gradient.

Results

Between March 1, 2020, and June 30, 2021, 348 patients were hospitalized with COVID-19 (Table 1). The mean (SD) age was 68.4 (13.9) years, 313 patients (90.2%) were male, 281 patients (83.4%) were Black, 47 patients (13.6%) were White, and 16 patients (4.8%) were Hispanic. One hundred forty patients (40.2%) resided in Washington, DC, 151 (43.4%) in Maryland, and 19 (5.5%) in Virginia. HFO was received by 86 patients (24.7%), 33 (9.5%) required intubation and mechanical ventilation, and 57 (16.4%) died. All intubations and deaths occurred among patients aged > 50 years, with death occurring in 17.8% of patients aged > 50 years.

Demographic characteristics and baseline comorbidities associated with COVID-19 disease severity can be found in eAppendix 2. In unadjusted analyses, age was significantly associated with the risk of HFO, with a mean (SD) age of 72.5 (11.7) years among those requiring HFO and 67.1 (14.4) years among patients without HFO (odds ratio [OR], 1.03; 95% CI, 1.01-1.05; P = .002). Although age was not associated with the risk of intubation, it was significantly associated with mortality. Patients who died had a mean (SD) age of 76.8 (11.8) years compared with 66.8 (13.7) years among survivors (OR, 1.06; 95% CI, 1.04-1.09; P < .001).

Compared with patients with no comorbidities, CCI categories of mild, moderate, and severe were associated with increased risk of requiring HFO (eAppendix 3). The adjusted OR (aOR) was highest among patients with severe CCI (aOR, 7.00; 95% CI, 2.42-20.32; P = .0007). In age-adjusted analyses, CCI was not associated with intubation or mortality.

Geospatial Analyses

State of residence, county of residence, and geographic area (including Washington, DC wards, and geographic divisions within counties of residence in Maryland and Virginia) were not associated with the clinical outcomes studied (eAppendix 4). However, zip code-based median income, analyzed as a continuous variable, was associated with a reduced likelihood of receiving HFO (aOR, 0.91; 95% CI, 0.84-0.99; P = .03). Income was not significantly associated with intubation or mortality.

The majority of patients hospitalized for COVID-19 at WVAMC resided in zip codes in eastern Washington, DC, inclusive of wards 7 and 8, and Prince George’s County, Maryland (Figure 1). These areas also corresponded to the lowest median household income by zip code (Figure 2).

Multivariable Analysis

Significant predictors of HFO requirement included comorbid diabetes (OR, 2.42; 95% CI, 1.27-4.61; P = .006) and liver disease or cirrhosis (OR, 2.19; 95% CI, 1.09-4.39; P = .02) (Table 2). CDC admission period was also associated with HFO need. Patients admitted after early 2020 had lower odds of receiving HFO. Race and median income based on zip code residence were not associated with HFO requirement.

Comorbid liver disease or cirrhosis was a significant predictor of intubation (OR, 2.81; 95% CI, 1.07-7.40; P = .03). CDC admission period was associated with intubation with lower odds of intubation for patients admitted after early 2020. Race and median income by zip code were not associated with intubation.

Significant predictors of mortality included age (OR, 2.20; 95% CI, 1.55-3.14; P = .0001), comorbid liver disease or cirrhosis (OR, 2.97; 95% CI, 1.31-6.74; P = .008), and OSA (OR, 3.45; 95% CI, 1.49-7.97; P = .003). CDC admission period was associated with mortality, with lower odds of intubation for patients admitted in mid- and late 2020. Race and median income by zip code residence were not associated with intubation.

Discussion

In this study of COVID-19 disease severity at a large integrated health care system that provides equal access to care, race, ethnicity, and geographic location were not associated with the need for HFO, intubation, or presumed mortality. Median income by zip code residence was associated with reduced HFO use in univariable analyses but not in multivariable models.

These findings support existing literature suggesting that race and ethnicity alone do not explain disparities in COVID-19 outcomes. Multiple studies have demonstrated that disparities in health outcomes have been reduced for patients receiving VHA care.^6,16-19 However, even within a health care system with assumed equal access, the finding of an association between income and need for HFO in the univariable analysis may reflect a greater likelihood of delays in care due to structural barriers. Multiple studies suggest low SES may be an independent risk factor for severe COVID-19 disease. Individuals with low SES have higher rates of chronic diseases of obesity, diabetes, heart disease, and lung disease; thus, they are also at greater risk of serious illness with COVID-19.^20-24 Socioeconomic disadvantage may also have limited individuals’ ability to engage in protective behaviors to reduce COVID-19 infection risk, including food stockpiling, social distancing, avoidance of public transportation, and refraining from working in “essential jobs.”²¹

Beyond SES, place of residence also influences health outcomes. Prior literature supports using zip codes to assess area-based SES status and monitor health disparities.²⁵ The Social Vulnerability Index incorporates SES factors for communities and measures social determinates of health at a zip code level exclusive of race and ethnicity.²⁶ Socially vulnerable communities are known to have higher rates of chronic diseases, COVID-19 mortality, and lower vaccination rates.³ Within a defined geographic area, an individual’s outcome for COVID-19 can be influenced by individual resources such as access to care and median income. Disposable income may mitigate COVID-19 risk by facilitating timely care, reducing occupational exposure, improving housing stability, and supporting health-promoting behaviors.²¹

Limitations

Due to the evolving nature of the COVID-19 pandemic, variants, treatments, and interventions varied throughout the study period and are not included in this analysis. In late December 2020, COVID-19 vaccination was approved with a tiered allocation for at-risk patients and direct health care professionals. Three of the 4 study periods analyzed in this study were prior to vaccine rollout and therefore vaccination history was not assessed. However, we tried to capture the evolving changes in COVID-19 variants, treatments and interventions, and skill in treating the disease through use of CDC-defined time frames. Another limitation is that some studies have shown that use of median income by zip code residence can underestimate mortality.²⁷ Also, shared resources and access to other sources of disposable income can impact the immediate attainment of social needs. For example, during the COVID-19 pandemic, health care systems in Washington, DC assisted vulnerable individuals by providing food, housing, and other resources.^28,29 Finally, the modest sample size limits generalizability and power to detect differences for certain variables, including Hispanic ethnicity.

Conclusions

There have been widely described disparities in disease severity and death during the COVID-19 pandemic. In this urban veteran cohort of hospitalized patients, there was no difference in the need for intubation or mortality associated with race. The findings suggest that a lower median income by zip code residence may be associated with greater disease severity at presentation, but do not predict severe outcomes and mortality overall. VHA care, which provides equal access to care, may mitigate the disparities seen in the private sector.

Large epidemiologic studies have shown disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status (SES). Racial and ethnic minorities and individuals of lower SES have experienced disproportionately higher rates of intensive care unit (ICU) admission and death. In Washington, DC, Black individuals (47% of the population) accounted for 51% of COVID-19 cases and 75% of deaths. In comparison, White individuals (41% of the population) accounted for 21% of cases and 11% of deaths.¹ Place of residence, such as living in socially vulnerable communities, has also been shown to be associated with higher rates of COVID-19 mortality and lower vaccination rates.^2-4 Social and structural inequities, such as limited access to health care services and mistrust of the health care system, may explain some of the observed disparities.⁵ However, data are limited regarding COVID-19 outcomes for individuals with equal access to care.

The Veterans Health Administration (VHA) is the largest integrated US health care system and operates 123 acute care hospitals. Previous research has demonstrated that disparities in outcomes for other diseases are attenuated or erased among veterans receiving VHA care.^6,7 Based on literature from the pandemic, markers of health care inequity relating to SES (eg, place of residence, median income) are expected to impact the outcomes of patients acutely hospitalized with COVID-19.⁴ We hypothesized that the impact on clinical outcomes of infection would be mitigated for veterans receiving VHA care.

This retrospective cohort study included veterans who presented to Washington Veterans Affairs Medical Center (WVAMC) with the goal of determining whether place of residence as a marker of SES, health care access, and median income were predictive of COVID-19 disease severity.

Methods

The WVAMC serves about 125,000 veterans across the metropolitan area, including parts of Maryland and Virginia. It is a high-complexity hospital with 164 acute care beds, 30 psychosocial residential rehabilitation beds, and an adjacent 120-bed community living center providing long-term, hospice, and palliative care.⁸

The WVAMC developed a dashboard that tracked patients with COVID-19 through on-site testing by admission date, ward, and other key demographics (PowerBi, Corporate Data Warehouse). All patients admitted to WVAMC with a diagnosis of COVID-19 between March 1, 2020, and June 30, 2021, were included in this retrospective review. Using the Computerized Patient Record System (CPRS) and the dashboard, we collected demographic information, baseline clinical diagnoses, laboratory results, and clinical interventions for all patients with documented COVID-19 infection as established by laboratory testing methods available at the time of diagnosis. Veterans treated exclusively outside the WVAMC were excluded. Hospitalization was defined as any acute inpatient admission or transfer recorded within 5 days before and 30 days after the laboratory collection of a positive COVID-19 test. Home testing kits were not widely available during the study period. An ICU stay was defined as any inpatient admission or transfer recorded within 5 days before or 30 days after the laboratory collection of a positive COVID-19 test for which the ward location had the specialty of medical or surgical ICU. Death due to COVID-19 was defined as occurring within 42 days (6 weeks) of a positive COVID-19 test.⁹ This definition assumed that during the peak of the pandemic, COVID-19 was the attributable cause of death, despite the possible contribution of underlying health conditions.

Patients’ admission periods were based on US Centers for Disease Control and Prevention (CDC) national data and classified as early 2020 (January 2020–April 2020), mid-2020 (May 2020–August 2020), late 2020 (September 2020–December 2020), and early 2021 (January 2021–April 2021).¹⁰ We chose to use these time periods as surrogates for the frequent changes in circulating COVID-19 variants, surges in case numbers, therapies and interventions available during the pandemic. The dominant COVID-19 variant during the study period was Alpha (B.1.17). Beta (B.1.351) variants were circulating infrequently, and Delta and Omicron appeared after the study period.¹¹ Treatment strategies evolved rapidly with emerging evidence, including the use of dexamethasone, beginning in June 2020.¹² WVAMC followed the Advisory Committee on Immunization Practices guidance on vaccination rollout beginning in December 2020.¹³

Patients' income was estimated by the median household income of the zip code residence based on US Census Bureau 2021 estimates and was assessed as both a continuous and categorical variable.¹⁴ The Charlson Comorbidity Index (CCI) was included in models as a continuous variable.¹⁵ Variables contributing to the CCI include myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, hemiplegia or paraplegia, ulcer disease, hepatic disease, diabetes (with or without end-organ damage), chronic obstructive pulmonary disease (COPD), connective tissue disease, leukemia, lymphoma, moderate or severe renal disease, solid tumor (with or without metastases), and HIV/AIDS. The WVAMC Institutional Review Board approved this study (IRB #1573071).

Variables

This study assessed 3 primary outcomes as indicators of disease severity during hospitalization: need for high-flow oxygen (HFO), intubation, and presumed mortality at any time during hospitalization. The following variables were collected as potential social determinants or clinical risk-adjustment predictors of disease severity outcomes: age; sex; race and ethnicity; median income for patient’s zip code residence, state, and county; wards within Washington, DC; comorbidities, CCI; tobacco use; and body mass index.¹⁵ Although medications at baseline, treatments during hospitalization for COVID-19, and laboratory parameters during hospitalization are shown in eAppendices 1 and 2, they are beyond the scope of this analysis.

Statistical Analysis

Three types of logistic regression models were calculated for predicting the disease severity outcomes: (1) simple unadjusted models; (2) models predicting from single variables plus age (age-adjusted); and (3) multivariable models using all nonredundant potential predictors with adequate sample sizes (multivariable). Variables were considered to have inadequate sample sizes if there was nontrivial missing data or small numbers within categories, (eg, AIDS, connective tissue disease). Potential predictors for the multivariable model included age, sex, race, median income by zip code residence, CCI, CDC admission period, obesity, hypertension, chronic kidney disease, obstructive sleep apnea (OSA), diabetes, COPD or asthma, liver disease, antibiotics, and acute kidney injury.

For the multivariable models, the following modifications were made to avoid unreliable parameter estimation and computation problems (quasi-separation): age and CCI were included as continuous rather than categorical variables. Race was recoded as a 2-category variable (Black vs other [White, Hispanic, American Indian, Alaska Native, Asian, Native Hawaiian, and Pacific Islander]), and ethnicity was excluded because of the small number of patients in this group (n = 16). Admission period was included. Predicted probability plots were generated for each outcome with continuous independent predictors (income and CCI), both unadjusted and adjusted for age as a continuous covariate. All analyses were performed using SAS version 9.4.

Heat Maps

Heat maps were generated to visualize the geospatial distribution of COVID-19 cases and median incomes across zip codes in the greater Washington, DC area. Patient case data and median income, aggregated by zip code, were imported using ArcGIS Online. A zip code boundary layer from Esri (United States Zip Code Boundaries) was used to spatially align the case data. Data were joined by matching zip codes or median incomes in the patient dataset to those in the boundary layer. The resulting polygon layer was styled using the Counts and Amounts (Color) symbology in ArcGIS Online, with case counts or median income determining the intensity of the color gradient.

Results

Between March 1, 2020, and June 30, 2021, 348 patients were hospitalized with COVID-19 (Table 1). The mean (SD) age was 68.4 (13.9) years, 313 patients (90.2%) were male, 281 patients (83.4%) were Black, 47 patients (13.6%) were White, and 16 patients (4.8%) were Hispanic. One hundred forty patients (40.2%) resided in Washington, DC, 151 (43.4%) in Maryland, and 19 (5.5%) in Virginia. HFO was received by 86 patients (24.7%), 33 (9.5%) required intubation and mechanical ventilation, and 57 (16.4%) died. All intubations and deaths occurred among patients aged > 50 years, with death occurring in 17.8% of patients aged > 50 years.

Demographic characteristics and baseline comorbidities associated with COVID-19 disease severity can be found in eAppendix 2. In unadjusted analyses, age was significantly associated with the risk of HFO, with a mean (SD) age of 72.5 (11.7) years among those requiring HFO and 67.1 (14.4) years among patients without HFO (odds ratio [OR], 1.03; 95% CI, 1.01-1.05; P = .002). Although age was not associated with the risk of intubation, it was significantly associated with mortality. Patients who died had a mean (SD) age of 76.8 (11.8) years compared with 66.8 (13.7) years among survivors (OR, 1.06; 95% CI, 1.04-1.09; P < .001).

Compared with patients with no comorbidities, CCI categories of mild, moderate, and severe were associated with increased risk of requiring HFO (eAppendix 3). The adjusted OR (aOR) was highest among patients with severe CCI (aOR, 7.00; 95% CI, 2.42-20.32; P = .0007). In age-adjusted analyses, CCI was not associated with intubation or mortality.

Geospatial Analyses

State of residence, county of residence, and geographic area (including Washington, DC wards, and geographic divisions within counties of residence in Maryland and Virginia) were not associated with the clinical outcomes studied (eAppendix 4). However, zip code-based median income, analyzed as a continuous variable, was associated with a reduced likelihood of receiving HFO (aOR, 0.91; 95% CI, 0.84-0.99; P = .03). Income was not significantly associated with intubation or mortality.

The majority of patients hospitalized for COVID-19 at WVAMC resided in zip codes in eastern Washington, DC, inclusive of wards 7 and 8, and Prince George’s County, Maryland (Figure 1). These areas also corresponded to the lowest median household income by zip code (Figure 2).

Multivariable Analysis

Significant predictors of HFO requirement included comorbid diabetes (OR, 2.42; 95% CI, 1.27-4.61; P = .006) and liver disease or cirrhosis (OR, 2.19; 95% CI, 1.09-4.39; P = .02) (Table 2). CDC admission period was also associated with HFO need. Patients admitted after early 2020 had lower odds of receiving HFO. Race and median income based on zip code residence were not associated with HFO requirement.

Comorbid liver disease or cirrhosis was a significant predictor of intubation (OR, 2.81; 95% CI, 1.07-7.40; P = .03). CDC admission period was associated with intubation with lower odds of intubation for patients admitted after early 2020. Race and median income by zip code were not associated with intubation.

Significant predictors of mortality included age (OR, 2.20; 95% CI, 1.55-3.14; P = .0001), comorbid liver disease or cirrhosis (OR, 2.97; 95% CI, 1.31-6.74; P = .008), and OSA (OR, 3.45; 95% CI, 1.49-7.97; P = .003). CDC admission period was associated with mortality, with lower odds of intubation for patients admitted in mid- and late 2020. Race and median income by zip code residence were not associated with intubation.

Discussion

In this study of COVID-19 disease severity at a large integrated health care system that provides equal access to care, race, ethnicity, and geographic location were not associated with the need for HFO, intubation, or presumed mortality. Median income by zip code residence was associated with reduced HFO use in univariable analyses but not in multivariable models.

These findings support existing literature suggesting that race and ethnicity alone do not explain disparities in COVID-19 outcomes. Multiple studies have demonstrated that disparities in health outcomes have been reduced for patients receiving VHA care.^6,16-19 However, even within a health care system with assumed equal access, the finding of an association between income and need for HFO in the univariable analysis may reflect a greater likelihood of delays in care due to structural barriers. Multiple studies suggest low SES may be an independent risk factor for severe COVID-19 disease. Individuals with low SES have higher rates of chronic diseases of obesity, diabetes, heart disease, and lung disease; thus, they are also at greater risk of serious illness with COVID-19.^20-24 Socioeconomic disadvantage may also have limited individuals’ ability to engage in protective behaviors to reduce COVID-19 infection risk, including food stockpiling, social distancing, avoidance of public transportation, and refraining from working in “essential jobs.”²¹

Beyond SES, place of residence also influences health outcomes. Prior literature supports using zip codes to assess area-based SES status and monitor health disparities.²⁵ The Social Vulnerability Index incorporates SES factors for communities and measures social determinates of health at a zip code level exclusive of race and ethnicity.²⁶ Socially vulnerable communities are known to have higher rates of chronic diseases, COVID-19 mortality, and lower vaccination rates.³ Within a defined geographic area, an individual’s outcome for COVID-19 can be influenced by individual resources such as access to care and median income. Disposable income may mitigate COVID-19 risk by facilitating timely care, reducing occupational exposure, improving housing stability, and supporting health-promoting behaviors.²¹

Limitations

Due to the evolving nature of the COVID-19 pandemic, variants, treatments, and interventions varied throughout the study period and are not included in this analysis. In late December 2020, COVID-19 vaccination was approved with a tiered allocation for at-risk patients and direct health care professionals. Three of the 4 study periods analyzed in this study were prior to vaccine rollout and therefore vaccination history was not assessed. However, we tried to capture the evolving changes in COVID-19 variants, treatments and interventions, and skill in treating the disease through use of CDC-defined time frames. Another limitation is that some studies have shown that use of median income by zip code residence can underestimate mortality.²⁷ Also, shared resources and access to other sources of disposable income can impact the immediate attainment of social needs. For example, during the COVID-19 pandemic, health care systems in Washington, DC assisted vulnerable individuals by providing food, housing, and other resources.^28,29 Finally, the modest sample size limits generalizability and power to detect differences for certain variables, including Hispanic ethnicity.

Conclusions

There have been widely described disparities in disease severity and death during the COVID-19 pandemic. In this urban veteran cohort of hospitalized patients, there was no difference in the need for intubation or mortality associated with race. The findings suggest that a lower median income by zip code residence may be associated with greater disease severity at presentation, but do not predict severe outcomes and mortality overall. VHA care, which provides equal access to care, may mitigate the disparities seen in the private sector.

Acne keloidalis nuchae (AKN) classically presents as chronic inflammation of the hair follicles on the occipital scalp/nape of the neck manifesting as papules and pustules that may progress to keloidlike scarring.¹ Photographs depicting the typical clinical presentation of AKN are shown in the Figure. In the literature, AKN has been described as primarily occurring in postpubertal males of African descent.² Despite its similar name, AKN is not related to acne vulgaris.³ The underlying cause of AKN is hypothesized to be multifactorial, including inflammation, infection, and trauma.² Acne keloidalis nuchae is most common in males aged 14 to 50 years, which may indicate that increased androgens contribute to its development.³ In some cases, patients have reported developing AKN lesions after receiving a haircut or shaving, suggesting a potential role of trauma to the hair follicles and secondary infection.² Histopathology typically shows a perifollicular inflammatory infiltrate that obscures the hair follicles with associated proximal fibrosis.⁴ On physical examination, dermoscopy can be used to visualize perifollicular pustules and fibrosis, which appears white, in the early stages of AKN. Patients may present with tufted hairs in more advanced stages.⁵ Patients with AKN often describe the lesions as pruritic and painful.²

In this study, we evaluated the most common treatment regimens used over a 6-year period by patients in the Los Angeles County hospital system in California and their efficacy on AKN lesions. Our study includes one of the largest cohorts of patients reported to date and as such demonstrates the real-world effects that current treatment regimens for AKN have on patient outcomes nationwide.

Methods

We performed a retrospective cross-sectional analysis of patient medical records from the Los Angeles County hospital system i2b2 (i2b2 tranSMART Foundation) clinical data warehouse over a 6-year period (January 2017–January 2023). We used the International Statistical Classification of Diseases, Tenth Revision codes L73.0 (acne keloid) and L73.1 (pseudofolliculitis barbae) to conduct our search in order to identify as many patients with follicular disorders as possible to include in the study. Of the 478 total medical records we reviewed, 183 patients were included based on a diagnosis of AKN by a dermatologist.

We then collected data on patient demographics and treatments received, including whether patients had received monotherapy or combination therapy. Of the 183 patients we initially identified, 4 were excluded from the study because they had not received any treatment, and 78 were excluded because no treatment outcomes were documented. The 101 patients who were included had received either monotherapy or a combination of treatments. Treatment outcomes were categorized as either improvement in the number and appearance of papules and/or keloidlike plaques, maintenance of stable lesions (ie, well controlled), and/or resolution of lesions as documented by the treating physician. No patients had overall worsening of their disease.

Results

Of the 101 patients included in the study, 34 (33.7%) received a combination of topical, systemic, and procedural treatments; 34 (33.7%) received a combination of topical and procedural treatments; 17 (16.8%) were treated with topicals only; 13 (12.9%) were treated with a combination of topical and systemic treatments; and 3 (3.0%) were treated with monotherapy of either a topical, systemic, or procedural therapy. Systemic and/or procedural therapy combined with topicals was provided as a first-line treatment for 63 (62.4%) patients. Treatment escalation to systemic or procedural therapy for those who did not respond to topical treatment was observed in 23 (22.8%) patients. The average number of unique treatments received per patient was 3.67.

Clindamycin and clobetasol were the most prescribed topical treatments, doxycycline was the most prescribed systemic therapy, and intralesional (IL) triamcinolone was the most performed procedural therapy. The most common treatment regimens were topical clindamycin and clobetasol, topical clindamycin and clobetasol with IL triamcinolone, and topical clindamycin and clobetasol with both IL triamcinolone and doxycycline.

Improvement in AKN lesions was reported for the majority of patients with known treatment outcomes across all types of regimens. Ninety-eight percent (99/101) of patients had improvement in lesions, 55.5% (56/101) had well-controlled lesions, and 20.8% (21/101) achieved resolution of disease. The treatment outcomes are outlined in eTables 1 and 2.

Comment

Most clinicians opted for a multitherapy treatment regimen, and improvement was noted in most patients regardless of which regimen was chosen. As expected, patients who had mild or early disease generally received topical agents first, including most commonly a mid- to high-potency steroid, antibiotic, retinoid, and/or antifungal; specifically, clindamycin, clobetasol, and fluocinolone were the most common agents chosen. Patients with severe disease were more likely to receive systemic and/or procedural treatments, including oral antibiotics or IL steroid injections most commonly. Improvement was documented in the majority of patients using these treatment regimens, and some patients did achieve full resolution of disease.

Our data cannot be used to determine which treatment alone is most effective for patients with AKN, as the patients in our study had varying levels of disease activity and types of lesions, and most received combination therapy. What our data do show is that combination therapies often work well to control or improve disease, but also that current therapeutic options only rarely lead to full resolution of disease.

Limitations of our study included an inability to stratify disease, an inability to rigorously analyze specific treatment outcomes since most patients did not receive monotherapy. The strength of our study is its size, which allows us to show that many different treatment regimens currently are being employed by dermatologists to treat AKN, and most of these seem to be somewhat effective.

Conclusion

Acne keloidalis nuchae is difficult to treat due to a lack of understanding of which pathophysiologic mechanisms dominate in any given patient, a lack of good data on treatment outcomes, and the variability of ways that the disease manifests. Thus far, as shown by the patients described in this study, the most efficacious treatment regimens seem to be combination therapies that target the multifactorial causes of this disease. Physicians should continue to choose treatments based on disease severity and cutaneous manifestations, tailor their approach by accounting for patient preferences, and consider a multimodal approach to treatment.

Acne keloidalis nuchae (AKN) classically presents as chronic inflammation of the hair follicles on the occipital scalp/nape of the neck manifesting as papules and pustules that may progress to keloidlike scarring.¹ Photographs depicting the typical clinical presentation of AKN are shown in the Figure. In the literature, AKN has been described as primarily occurring in postpubertal males of African descent.² Despite its similar name, AKN is not related to acne vulgaris.³ The underlying cause of AKN is hypothesized to be multifactorial, including inflammation, infection, and trauma.² Acne keloidalis nuchae is most common in males aged 14 to 50 years, which may indicate that increased androgens contribute to its development.³ In some cases, patients have reported developing AKN lesions after receiving a haircut or shaving, suggesting a potential role of trauma to the hair follicles and secondary infection.² Histopathology typically shows a perifollicular inflammatory infiltrate that obscures the hair follicles with associated proximal fibrosis.⁴ On physical examination, dermoscopy can be used to visualize perifollicular pustules and fibrosis, which appears white, in the early stages of AKN. Patients may present with tufted hairs in more advanced stages.⁵ Patients with AKN often describe the lesions as pruritic and painful.²

In this study, we evaluated the most common treatment regimens used over a 6-year period by patients in the Los Angeles County hospital system in California and their efficacy on AKN lesions. Our study includes one of the largest cohorts of patients reported to date and as such demonstrates the real-world effects that current treatment regimens for AKN have on patient outcomes nationwide.

Methods

We performed a retrospective cross-sectional analysis of patient medical records from the Los Angeles County hospital system i2b2 (i2b2 tranSMART Foundation) clinical data warehouse over a 6-year period (January 2017–January 2023). We used the International Statistical Classification of Diseases, Tenth Revision codes L73.0 (acne keloid) and L73.1 (pseudofolliculitis barbae) to conduct our search in order to identify as many patients with follicular disorders as possible to include in the study. Of the 478 total medical records we reviewed, 183 patients were included based on a diagnosis of AKN by a dermatologist.

We then collected data on patient demographics and treatments received, including whether patients had received monotherapy or combination therapy. Of the 183 patients we initially identified, 4 were excluded from the study because they had not received any treatment, and 78 were excluded because no treatment outcomes were documented. The 101 patients who were included had received either monotherapy or a combination of treatments. Treatment outcomes were categorized as either improvement in the number and appearance of papules and/or keloidlike plaques, maintenance of stable lesions (ie, well controlled), and/or resolution of lesions as documented by the treating physician. No patients had overall worsening of their disease.

Results

Of the 101 patients included in the study, 34 (33.7%) received a combination of topical, systemic, and procedural treatments; 34 (33.7%) received a combination of topical and procedural treatments; 17 (16.8%) were treated with topicals only; 13 (12.9%) were treated with a combination of topical and systemic treatments; and 3 (3.0%) were treated with monotherapy of either a topical, systemic, or procedural therapy. Systemic and/or procedural therapy combined with topicals was provided as a first-line treatment for 63 (62.4%) patients. Treatment escalation to systemic or procedural therapy for those who did not respond to topical treatment was observed in 23 (22.8%) patients. The average number of unique treatments received per patient was 3.67.

Clindamycin and clobetasol were the most prescribed topical treatments, doxycycline was the most prescribed systemic therapy, and intralesional (IL) triamcinolone was the most performed procedural therapy. The most common treatment regimens were topical clindamycin and clobetasol, topical clindamycin and clobetasol with IL triamcinolone, and topical clindamycin and clobetasol with both IL triamcinolone and doxycycline.

Improvement in AKN lesions was reported for the majority of patients with known treatment outcomes across all types of regimens. Ninety-eight percent (99/101) of patients had improvement in lesions, 55.5% (56/101) had well-controlled lesions, and 20.8% (21/101) achieved resolution of disease. The treatment outcomes are outlined in eTables 1 and 2.

Comment

Most clinicians opted for a multitherapy treatment regimen, and improvement was noted in most patients regardless of which regimen was chosen. As expected, patients who had mild or early disease generally received topical agents first, including most commonly a mid- to high-potency steroid, antibiotic, retinoid, and/or antifungal; specifically, clindamycin, clobetasol, and fluocinolone were the most common agents chosen. Patients with severe disease were more likely to receive systemic and/or procedural treatments, including oral antibiotics or IL steroid injections most commonly. Improvement was documented in the majority of patients using these treatment regimens, and some patients did achieve full resolution of disease.

Our data cannot be used to determine which treatment alone is most effective for patients with AKN, as the patients in our study had varying levels of disease activity and types of lesions, and most received combination therapy. What our data do show is that combination therapies often work well to control or improve disease, but also that current therapeutic options only rarely lead to full resolution of disease.

Limitations of our study included an inability to stratify disease, an inability to rigorously analyze specific treatment outcomes since most patients did not receive monotherapy. The strength of our study is its size, which allows us to show that many different treatment regimens currently are being employed by dermatologists to treat AKN, and most of these seem to be somewhat effective.

Conclusion

Acne keloidalis nuchae is difficult to treat due to a lack of understanding of which pathophysiologic mechanisms dominate in any given patient, a lack of good data on treatment outcomes, and the variability of ways that the disease manifests. Thus far, as shown by the patients described in this study, the most efficacious treatment regimens seem to be combination therapies that target the multifactorial causes of this disease. Physicians should continue to choose treatments based on disease severity and cutaneous manifestations, tailor their approach by accounting for patient preferences, and consider a multimodal approach to treatment.

Acne keloidalis nuchae (AKN) classically presents as chronic inflammation of the hair follicles on the occipital scalp/nape of the neck manifesting as papules and pustules that may progress to keloidlike scarring.¹ Photographs depicting the typical clinical presentation of AKN are shown in the Figure. In the literature, AKN has been described as primarily occurring in postpubertal males of African descent.² Despite its similar name, AKN is not related to acne vulgaris.³ The underlying cause of AKN is hypothesized to be multifactorial, including inflammation, infection, and trauma.² Acne keloidalis nuchae is most common in males aged 14 to 50 years, which may indicate that increased androgens contribute to its development.³ In some cases, patients have reported developing AKN lesions after receiving a haircut or shaving, suggesting a potential role of trauma to the hair follicles and secondary infection.² Histopathology typically shows a perifollicular inflammatory infiltrate that obscures the hair follicles with associated proximal fibrosis.⁴ On physical examination, dermoscopy can be used to visualize perifollicular pustules and fibrosis, which appears white, in the early stages of AKN. Patients may present with tufted hairs in more advanced stages.⁵ Patients with AKN often describe the lesions as pruritic and painful.²

In this study, we evaluated the most common treatment regimens used over a 6-year period by patients in the Los Angeles County hospital system in California and their efficacy on AKN lesions. Our study includes one of the largest cohorts of patients reported to date and as such demonstrates the real-world effects that current treatment regimens for AKN have on patient outcomes nationwide.

Methods

We performed a retrospective cross-sectional analysis of patient medical records from the Los Angeles County hospital system i2b2 (i2b2 tranSMART Foundation) clinical data warehouse over a 6-year period (January 2017–January 2023). We used the International Statistical Classification of Diseases, Tenth Revision codes L73.0 (acne keloid) and L73.1 (pseudofolliculitis barbae) to conduct our search in order to identify as many patients with follicular disorders as possible to include in the study. Of the 478 total medical records we reviewed, 183 patients were included based on a diagnosis of AKN by a dermatologist.

We then collected data on patient demographics and treatments received, including whether patients had received monotherapy or combination therapy. Of the 183 patients we initially identified, 4 were excluded from the study because they had not received any treatment, and 78 were excluded because no treatment outcomes were documented. The 101 patients who were included had received either monotherapy or a combination of treatments. Treatment outcomes were categorized as either improvement in the number and appearance of papules and/or keloidlike plaques, maintenance of stable lesions (ie, well controlled), and/or resolution of lesions as documented by the treating physician. No patients had overall worsening of their disease.

Results

Of the 101 patients included in the study, 34 (33.7%) received a combination of topical, systemic, and procedural treatments; 34 (33.7%) received a combination of topical and procedural treatments; 17 (16.8%) were treated with topicals only; 13 (12.9%) were treated with a combination of topical and systemic treatments; and 3 (3.0%) were treated with monotherapy of either a topical, systemic, or procedural therapy. Systemic and/or procedural therapy combined with topicals was provided as a first-line treatment for 63 (62.4%) patients. Treatment escalation to systemic or procedural therapy for those who did not respond to topical treatment was observed in 23 (22.8%) patients. The average number of unique treatments received per patient was 3.67.

Clindamycin and clobetasol were the most prescribed topical treatments, doxycycline was the most prescribed systemic therapy, and intralesional (IL) triamcinolone was the most performed procedural therapy. The most common treatment regimens were topical clindamycin and clobetasol, topical clindamycin and clobetasol with IL triamcinolone, and topical clindamycin and clobetasol with both IL triamcinolone and doxycycline.

Improvement in AKN lesions was reported for the majority of patients with known treatment outcomes across all types of regimens. Ninety-eight percent (99/101) of patients had improvement in lesions, 55.5% (56/101) had well-controlled lesions, and 20.8% (21/101) achieved resolution of disease. The treatment outcomes are outlined in eTables 1 and 2.

Comment

Most clinicians opted for a multitherapy treatment regimen, and improvement was noted in most patients regardless of which regimen was chosen. As expected, patients who had mild or early disease generally received topical agents first, including most commonly a mid- to high-potency steroid, antibiotic, retinoid, and/or antifungal; specifically, clindamycin, clobetasol, and fluocinolone were the most common agents chosen. Patients with severe disease were more likely to receive systemic and/or procedural treatments, including oral antibiotics or IL steroid injections most commonly. Improvement was documented in the majority of patients using these treatment regimens, and some patients did achieve full resolution of disease.

Our data cannot be used to determine which treatment alone is most effective for patients with AKN, as the patients in our study had varying levels of disease activity and types of lesions, and most received combination therapy. What our data do show is that combination therapies often work well to control or improve disease, but also that current therapeutic options only rarely lead to full resolution of disease.

Limitations of our study included an inability to stratify disease, an inability to rigorously analyze specific treatment outcomes since most patients did not receive monotherapy. The strength of our study is its size, which allows us to show that many different treatment regimens currently are being employed by dermatologists to treat AKN, and most of these seem to be somewhat effective.

Conclusion

Acne keloidalis nuchae is difficult to treat due to a lack of understanding of which pathophysiologic mechanisms dominate in any given patient, a lack of good data on treatment outcomes, and the variability of ways that the disease manifests. Thus far, as shown by the patients described in this study, the most efficacious treatment regimens seem to be combination therapies that target the multifactorial causes of this disease. Physicians should continue to choose treatments based on disease severity and cutaneous manifestations, tailor their approach by accounting for patient preferences, and consider a multimodal approach to treatment.

The estimated prevalence of psoriasis in individuals older than 20 years in the United States has been reported at approximately 3%, or more than 7.5 million people.¹ There currently is no cure for psoriasis, and available therapeutics, including phototherapy,² topical therapies,³ systemic medications,⁴ and biologic agents,⁵ are focused only on controlling symptoms. The National Psoriasis Foundation defines an acceptable treatment response for plaque psoriasis as 3% or lower body surface area (BSA) involvement after 3 months of therapy, with a treat-to-target (TTT) goal of 1% or less BSA involvement.⁶

Cytokines are known to mediate psoriasis pathology, and biologic therapies target the signaling cascade of various cytokines. Biologics approved to treat moderate to severe plaque psoriasis include IgG monoclonal antibodies binding and inhibiting the activity of interleukin (IL)-17 (ixekizumab,⁷ secukinumab⁸), IL-23 (guselkumab,⁹ risankizumab,¹⁰ tildrakizumab¹¹), and IL-12/23 (ustekinumab¹²). Despite targeting these cytokines, biologics may not sufficiently suppress the symptoms of psoriatic disease and their severity in all patients. Adding a topical treatment to biologic therapy can augment clinical response without increasing the incidence of adverse effects^13-15 and may reduce the need to switch biologics due to ineffectiveness. Switching biologics likely would increase cost burden to the health care system and/or patient depending on their insurance plan and possibly introduce new safety and/or tolerability issues.^16,17

In patients who do not adequately respond to biologics, better responses were reported when topical medications including halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam^17,18 were administered. In randomized or open-label, real-world studies, patients with psoriasis responded well when topical medications were added to a biologic, such as tildrakizumab combined with halcinonide ointment 0.1%,¹⁹ etanercept combined with topical clobetasol propionate foam,²⁰ or adalimumab combined with calcipotriene/betamethasone dipropionate foam.²¹ No additional safety concerns were observed with the topical add-ons in any of these studies.

Tapinarof is an aryl hydrocarbon receptor agonist approved by the US Food and Drug Administration for topical treatment of plaque psoriasis in adults.²² It is a first-in-class small molecule with a novel mechanism of action that downregulates IL-17A and IL-17F and normalizes the skin barrier through expression of filaggrin, loricrin, and involucrin; it also has antioxidant activity.²³ In the phase 3 PSOARING 1 and 2 trials, daily application of tapinarof cream was safe and efficacious in patients with plaque psoriasis,^24,25 with a remittive (maintenance) effect of a median of approximately 4 months after discontinuation.²⁵ In these 2 phase 3 studies, tapinarof significantly (P<0.01 at week 12) relieved itch, which was seen rapidly (P<0.05 at week 2),²⁶ improved quality of life,²⁷ and led to high patient satisfaction.²⁷ When tapinarof cream was combined with deucravacitinib in a patient with severe plaque psoriasis, symptoms rapidly cleared, with a 75% decrease in disease severity after 4 weeks.²⁸

The objective of this prospective, open-label, real-world, single-center study was to assess the effectiveness, safety, and remittive (or maintenance) effect of nonsteroidal tapinarof cream 1% added to ongoing biologic therapy in patients with plaque psoriasis who were not adequately responding to a biologic alone.

Methods

Study Design and Participants—This prospective, open-label, real-world, single-center study assessed the safety and effectiveness of once-daily application of tapinarof cream 1% added to ongoing biologic therapy to help reach the National Psoriasis Foundation’s TTT goal of 1% or less BSA involvement at week 12 in patients with 3% or greater BSA involvement after taking the biologic for 24 weeks or more. The study protocol was approved by an institutional review board, and the study was conducted according to the ethical guidelines of the Declaration of Helsinki and Good Clinical Practice. All participants provided written informed consent before the study began.

Eligible participants were otherwise healthy males and females aged 18 years and older with moderate to severe plaque psoriasis (BSA involvement ≥3%) who had been treated with a biologic for 24 weeks or more. Patients were recruited from the Psoriasis Treatment Center of New Jersey (East Windsor, New Jersey). Exclusion criteria were recent use of oral systemic therapies (within 4 weeks of baseline) or topical therapies (within 2 weeks) to treat psoriasis, recent use of UVB (within 2 weeks) or psoralen plus UVA (within 4 weeks) phototherapy, or use of any investigational drug within 4 weeks of baseline (or within 5 pharmacokinetic/pharmacodynamic half-lives, whichever was longer). Patients who were pregnant or breastfeeding or who had any known hypersensitivity to the excipients of tapinarof cream also were excluded from the study.

Eligible participants received tapinarof cream 1% once daily plus their ongoing biologic for 12 weeks, after which tapinarof was discontinued and the biologic was continued for an additional 4 weeks. A remittive (maintenance) effect was assessed at week 16.

Study Outcomes—Safety and efficacy were evaluated at baseline and weeks 2, 4, 8, 12, and 16. The primary end point was the proportion of patients who reached the TTT goal of 1% or less BSA involvement at week 12. Secondary end points included the proportion of patients with 1% or less BSA involvement at weeks 2, 4, 8, and 16; and PGA scores, composite PGA multiplied by mean percentage of BSA involvement (PGA×BSA), and PASI scores at baseline and weeks 2, 4, 8, 12, and 16. The patient-reported outcomes of Dermatology Life Quality Index (DLQI) and Worst Itch Numeric Rating Scale (WI-NRS) scores also were evaluated at baseline and weeks 2, 4, 8, 12, and 16. In patients who had disease involvement on the scalp or genital region at baseline, Psoriasis Scalp Severity Index (PSSI) and Static Physician’s Global Assessment of Genitalia scores, respectively, were assessed at baseline and weeks 2, 4, 8, 12, and 16. Safety was determined by the incidence, severity, and relatedness of adverse events (AEs) and serious AEs.

Statistical Analysis—Approximately 30 participants were planned for enrollment and recruited consecutively as they were identified during screening against inclusion and exclusion criteria. Changes from baseline in all outcomes were summarized descriptively. Missing data were not imputed. Given the sample size, no formal statistical analyses were conducted. Safety was summarized by descriptively collating AEs and serious AEs, including their frequency, severity, and treatment relatedness.

Results

Thirty participants were enrolled in the study, and 20 fully completed the study. Nine discontinued treatment before week 12 (6 were lost to follow-up, 2 were terminated early by the investigators, and 1 voluntarily withdrew); 1 additional participant was lost to follow-up after week 12. Patients were predominantly male (20/30 [66.7%]) and White (21/30 [70.0%]); the mean age of all participants was 55.4 years, and the mean (SD) duration of psoriasis was 21.4 (15.0) years (Table 1). The mean baseline percentage of BSA involvement and mean baseline PGA, PASI, and DLQI scores are shown in Table 1. Most (19/30 [63.3%]) patients received biologics that inhibited IL-23 activity (guselkumab, risankizumab, tildrakizumab), approximately one-third (9/30 [30.0%]) received biologics that inhibited IL-17 activity (ixekizumab, secukinumab), and 2 (6.7%) received biologics that inhibited IL-12/IL-23 activity (ustekinumab)(Table 1).

For the primary end point, 52.4% (11/21) of patients reached the TTT goal (BSA involvement ≤1% after 12 weeks of treatment with tapinarof cream added to a prescribed biologic). The proportion of patients reaching the TTT goal increased over time with the combined treatment (eFigure 1). Additionally, the mean percentage of BSA involvement (eFigure 2) as well as the mean values for PGA (eFigure 3) and PGA×BSA decreased over time. The mean percentage of BSA involvement was 5.0% at baseline and dropped to 2.0% by week 12. Similar reductions were observed for PGA and PGA×BSA scores at week 12.

After discontinuing tapinarof cream at week 12 and receiving only the biologic for 4 weeks, the proportion of patients maintaining 1% or less BSA involvement fell to 40.0% (8/20) at week 16, which was closer to that observed at week 8 (36% [9/25]) than at week 12 (52.4% [11/21])(eFigure 1).

The mean PASI score was 5.5 at baseline, then decreased over time when tapinarof cream was combined with a biologic (eFigure 4), falling to 3.1 by week 2 and 1.6 by week 12; it was maintained at 1.7 at week 16. Nine (30.0%) participants had psoriasis on the scalp at baseline with a mean PSSI score of 2.6, which decreased to 0.83 by week 2. By week 12, the mean PSSI score remained stable at 0.95 in the 2 (9.5%) participants who still had scalp involvement. The mean PSSI score increased slightly to 1.45 after patients received only the biologic for 4 weeks. At baseline, 3 (10.0%) patients had genital involvement (mean Static Physician’s Global Assessment of Genitalia score, 0.27). Symptoms resolved in 2 (66.7%) of these patients at week 2 and stayed consistent until week 16; the third patient withdrew at week 2.

Both DLQI and WI-NRS scores decreased with use of tapinarof cream added to a biologic up to week 12 (eFigures 5 and 6). Mean DLQI scores were 5.3 at baseline and 3.1 at week 12. At week 16, the mean DLQI score remained stable at 2.8. Mean WI-NRS scores decreased from 4.0 at baseline to 2.7 at week 12 with the therapy combination; at week 16, the mean WI-NRS score fell further to 1.8.

A total of 6 AEs were reported in 5 (16.7%) patients (Table 2). The majority (4/6 [67.0%]) of AEs were considered mild. Two reported cases of COVID-19 were both considered mild and unrelated. Mild folliculitis and moderate worsening of psoriasis in 2 (6.7%) different patients were the only AEs considered related to treatment. No serious AEs were reported, and no patient withdrew from the study due to an AE.

Comment

In this prospective, open-label, real-world study, we found that when a patient’s response to a biologic is unsatisfactory, adding nonsteroidal tapinarof cream can enhance the treatment effect of the biologic. More than half of patients who were not adequately responding to a biologic reached the TTT goal at week 12, which was maintained in most of the responders for 4 weeks after tapinarof discontinuation. All measures of disease activity and quality of life (measured by the DLQI) improved when tapinarof was introduced, and the combination was well tolerated and without any unexpected safety signals.

Disease activity improvements we observed with the nonsteroidal tapinarof cream were consistent with those reported when topical steroidal therapies were given to patients responding poorly to their current biologic. Our primary end point (proportion of patients with BSA involvement ≤1% after 12 weeks) showed that half (52% [11/21]) of patients whose BSA involvement was 3% or greater with a biologic for 24 weeks or more reached the TTT goal after 12 weeks of tapinarof-biologic treatment. Other studies of halobetasol propionate–tazarotene lotion¹⁶ and calcipotriene/betamethasone dipropionate foam^17,18 added to the current biologic of poor responders found 60% to 68% of patients had reductions in their percentage BSA to 1% or lower at 12 to 16 weeks of treatment. Randomized studies showed etanercept plus topical clobetasol propionate foam²⁰ or adalimumab plus calcipotriene/betamethasone dipropionate foam²¹ similarly enhanced treatment effects vs biologic alone.

A phase 3 PSOARING trial demonstrated benefit from treatment with tapinarof alone, with a remittive effect of approximately 4 months after discontinuation.²⁵ Our data are consistent with these findings, with 40% (8/20) of patients demonstrating a remittive effect 4 weeks after discontinuing tapinarof while receiving a biologic. A similar maintenance effect was reported in another study in 50% (9/18) of patients treated with a biologic plus halobetasol propionate–tazarotene lotion.¹⁶ Additionally, when halcinonide ointment was given to patients receiving tildrakizumab, mean percentage of BSA involvement, PGA scores, PGA×BSA, and DLQI scores improved and were maintained 4 weeks after halcinonide ointment was stopped.¹⁹ Thus, topical therapy can augment and extend a biologic’s effect for up to 4 weeks. While a longer remittive effect is possible in our patients based on the 4-month remittive rate observed in the PSOARING trials,²⁵ further patient observation would be needed to confirm.

In our study, tapinarof cream added to a biologic had a good safety and tolerability profile. Few AEs were recorded, with most being mild in nature, and no serious AEs or discontinuations due to AEs were reported. Only 1 case of mild folliculitis and 1 case of moderate worsening of psoriasis were considered treatment related. Further, no unexpected or new safety signals with the tapinarof-biologic combination were observed compared with tapinarof alone.²⁷Prior studies have found that supplementing a biologic with topical therapy can reduce the probability of patients switching to another biologic.^16,19 We previously found that adding halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam¹⁷ to a biologic helped reduce the probability of switching biologics from 88% to 90% at baseline to 12% to 24% after 12 weeks of combined therapy. Such combinations also could prevent a less responsive patient from being prescribed a higher biologic dose.¹⁹ These are important research findings, as patients—even when not responding well to their current biologic—are more likely to be tolerating that biologic well, and switching to a new biologic may introduce new safety or tolerability concerns. Thus, by enhancing the effect of a biologic with a topical therapy, one can avoid increasing the dose of the current biologic or switching to a new biologic, either of which may increase safety and/or tolerability risks. Switching biologics also has increased cost implications to the health care system and/or the patient. When comparing the cost of adding halobetasol propionate–tazarotene lotion to a biologic compared with switching to another biologic, the cost was 1.2 to 2.9 times higher to switch, depending on the biologic, compared with a smaller incremental cost increase to add a topical to the current biologic.¹⁶ Similar observations were reported with calcipotriene/betamethasone dipropionate foam plus a biologic.¹⁷ Although we did not evaluate biologic switching here, we anticipate a similar clinical scenario with a tapinarof-biologic combination.

Limitations of our study included the open-label design, lack of a control arm, and the relatively small study population; however, for studies investigating the safety and effectiveness of a treatment in a real-world setting, these limitations are common and are not unexpected. Our results also are consistent with the overall improvement seen in other studies^16-21 examining the effects of adding a topical to a biologic. Future research is warranted to investigate a longer remittive effect and potential health care system and patient cost savings without having to switch biologics due to lack of effectiveness.

Conclusion

This study demonstrated that adjunctive use of nonsteroidal tapinarof cream 1% may enhance a biologic treatment effect in patients with moderate to severe plaque psoriasis, providing an adequate response for many patients who were not responding well to a biologic alone. Clinical outcomes improved with the tapinarof-biologic combination, and a remittive effect was noted 4 weeks after tapinarof discontinuation without any new safety signals. Adding tapinarof cream to a biologic also may prevent the need to switch biologics when patients do not sufficiently respond, preserving the safety and cost associated with a patient’s current biologic.

The estimated prevalence of psoriasis in individuals older than 20 years in the United States has been reported at approximately 3%, or more than 7.5 million people.¹ There currently is no cure for psoriasis, and available therapeutics, including phototherapy,² topical therapies,³ systemic medications,⁴ and biologic agents,⁵ are focused only on controlling symptoms. The National Psoriasis Foundation defines an acceptable treatment response for plaque psoriasis as 3% or lower body surface area (BSA) involvement after 3 months of therapy, with a treat-to-target (TTT) goal of 1% or less BSA involvement.⁶

Cytokines are known to mediate psoriasis pathology, and biologic therapies target the signaling cascade of various cytokines. Biologics approved to treat moderate to severe plaque psoriasis include IgG monoclonal antibodies binding and inhibiting the activity of interleukin (IL)-17 (ixekizumab,⁷ secukinumab⁸), IL-23 (guselkumab,⁹ risankizumab,¹⁰ tildrakizumab¹¹), and IL-12/23 (ustekinumab¹²). Despite targeting these cytokines, biologics may not sufficiently suppress the symptoms of psoriatic disease and their severity in all patients. Adding a topical treatment to biologic therapy can augment clinical response without increasing the incidence of adverse effects^13-15 and may reduce the need to switch biologics due to ineffectiveness. Switching biologics likely would increase cost burden to the health care system and/or patient depending on their insurance plan and possibly introduce new safety and/or tolerability issues.^16,17

In patients who do not adequately respond to biologics, better responses were reported when topical medications including halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam^17,18 were administered. In randomized or open-label, real-world studies, patients with psoriasis responded well when topical medications were added to a biologic, such as tildrakizumab combined with halcinonide ointment 0.1%,¹⁹ etanercept combined with topical clobetasol propionate foam,²⁰ or adalimumab combined with calcipotriene/betamethasone dipropionate foam.²¹ No additional safety concerns were observed with the topical add-ons in any of these studies.

Tapinarof is an aryl hydrocarbon receptor agonist approved by the US Food and Drug Administration for topical treatment of plaque psoriasis in adults.²² It is a first-in-class small molecule with a novel mechanism of action that downregulates IL-17A and IL-17F and normalizes the skin barrier through expression of filaggrin, loricrin, and involucrin; it also has antioxidant activity.²³ In the phase 3 PSOARING 1 and 2 trials, daily application of tapinarof cream was safe and efficacious in patients with plaque psoriasis,^24,25 with a remittive (maintenance) effect of a median of approximately 4 months after discontinuation.²⁵ In these 2 phase 3 studies, tapinarof significantly (P<0.01 at week 12) relieved itch, which was seen rapidly (P<0.05 at week 2),²⁶ improved quality of life,²⁷ and led to high patient satisfaction.²⁷ When tapinarof cream was combined with deucravacitinib in a patient with severe plaque psoriasis, symptoms rapidly cleared, with a 75% decrease in disease severity after 4 weeks.²⁸

The objective of this prospective, open-label, real-world, single-center study was to assess the effectiveness, safety, and remittive (or maintenance) effect of nonsteroidal tapinarof cream 1% added to ongoing biologic therapy in patients with plaque psoriasis who were not adequately responding to a biologic alone.

Methods

Study Design and Participants—This prospective, open-label, real-world, single-center study assessed the safety and effectiveness of once-daily application of tapinarof cream 1% added to ongoing biologic therapy to help reach the National Psoriasis Foundation’s TTT goal of 1% or less BSA involvement at week 12 in patients with 3% or greater BSA involvement after taking the biologic for 24 weeks or more. The study protocol was approved by an institutional review board, and the study was conducted according to the ethical guidelines of the Declaration of Helsinki and Good Clinical Practice. All participants provided written informed consent before the study began.

Eligible participants were otherwise healthy males and females aged 18 years and older with moderate to severe plaque psoriasis (BSA involvement ≥3%) who had been treated with a biologic for 24 weeks or more. Patients were recruited from the Psoriasis Treatment Center of New Jersey (East Windsor, New Jersey). Exclusion criteria were recent use of oral systemic therapies (within 4 weeks of baseline) or topical therapies (within 2 weeks) to treat psoriasis, recent use of UVB (within 2 weeks) or psoralen plus UVA (within 4 weeks) phototherapy, or use of any investigational drug within 4 weeks of baseline (or within 5 pharmacokinetic/pharmacodynamic half-lives, whichever was longer). Patients who were pregnant or breastfeeding or who had any known hypersensitivity to the excipients of tapinarof cream also were excluded from the study.

Eligible participants received tapinarof cream 1% once daily plus their ongoing biologic for 12 weeks, after which tapinarof was discontinued and the biologic was continued for an additional 4 weeks. A remittive (maintenance) effect was assessed at week 16.

Study Outcomes—Safety and efficacy were evaluated at baseline and weeks 2, 4, 8, 12, and 16. The primary end point was the proportion of patients who reached the TTT goal of 1% or less BSA involvement at week 12. Secondary end points included the proportion of patients with 1% or less BSA involvement at weeks 2, 4, 8, and 16; and PGA scores, composite PGA multiplied by mean percentage of BSA involvement (PGA×BSA), and PASI scores at baseline and weeks 2, 4, 8, 12, and 16. The patient-reported outcomes of Dermatology Life Quality Index (DLQI) and Worst Itch Numeric Rating Scale (WI-NRS) scores also were evaluated at baseline and weeks 2, 4, 8, 12, and 16. In patients who had disease involvement on the scalp or genital region at baseline, Psoriasis Scalp Severity Index (PSSI) and Static Physician’s Global Assessment of Genitalia scores, respectively, were assessed at baseline and weeks 2, 4, 8, 12, and 16. Safety was determined by the incidence, severity, and relatedness of adverse events (AEs) and serious AEs.

Statistical Analysis—Approximately 30 participants were planned for enrollment and recruited consecutively as they were identified during screening against inclusion and exclusion criteria. Changes from baseline in all outcomes were summarized descriptively. Missing data were not imputed. Given the sample size, no formal statistical analyses were conducted. Safety was summarized by descriptively collating AEs and serious AEs, including their frequency, severity, and treatment relatedness.

Results

Thirty participants were enrolled in the study, and 20 fully completed the study. Nine discontinued treatment before week 12 (6 were lost to follow-up, 2 were terminated early by the investigators, and 1 voluntarily withdrew); 1 additional participant was lost to follow-up after week 12. Patients were predominantly male (20/30 [66.7%]) and White (21/30 [70.0%]); the mean age of all participants was 55.4 years, and the mean (SD) duration of psoriasis was 21.4 (15.0) years (Table 1). The mean baseline percentage of BSA involvement and mean baseline PGA, PASI, and DLQI scores are shown in Table 1. Most (19/30 [63.3%]) patients received biologics that inhibited IL-23 activity (guselkumab, risankizumab, tildrakizumab), approximately one-third (9/30 [30.0%]) received biologics that inhibited IL-17 activity (ixekizumab, secukinumab), and 2 (6.7%) received biologics that inhibited IL-12/IL-23 activity (ustekinumab)(Table 1).

For the primary end point, 52.4% (11/21) of patients reached the TTT goal (BSA involvement ≤1% after 12 weeks of treatment with tapinarof cream added to a prescribed biologic). The proportion of patients reaching the TTT goal increased over time with the combined treatment (eFigure 1). Additionally, the mean percentage of BSA involvement (eFigure 2) as well as the mean values for PGA (eFigure 3) and PGA×BSA decreased over time. The mean percentage of BSA involvement was 5.0% at baseline and dropped to 2.0% by week 12. Similar reductions were observed for PGA and PGA×BSA scores at week 12.

After discontinuing tapinarof cream at week 12 and receiving only the biologic for 4 weeks, the proportion of patients maintaining 1% or less BSA involvement fell to 40.0% (8/20) at week 16, which was closer to that observed at week 8 (36% [9/25]) than at week 12 (52.4% [11/21])(eFigure 1).

The mean PASI score was 5.5 at baseline, then decreased over time when tapinarof cream was combined with a biologic (eFigure 4), falling to 3.1 by week 2 and 1.6 by week 12; it was maintained at 1.7 at week 16. Nine (30.0%) participants had psoriasis on the scalp at baseline with a mean PSSI score of 2.6, which decreased to 0.83 by week 2. By week 12, the mean PSSI score remained stable at 0.95 in the 2 (9.5%) participants who still had scalp involvement. The mean PSSI score increased slightly to 1.45 after patients received only the biologic for 4 weeks. At baseline, 3 (10.0%) patients had genital involvement (mean Static Physician’s Global Assessment of Genitalia score, 0.27). Symptoms resolved in 2 (66.7%) of these patients at week 2 and stayed consistent until week 16; the third patient withdrew at week 2.

Both DLQI and WI-NRS scores decreased with use of tapinarof cream added to a biologic up to week 12 (eFigures 5 and 6). Mean DLQI scores were 5.3 at baseline and 3.1 at week 12. At week 16, the mean DLQI score remained stable at 2.8. Mean WI-NRS scores decreased from 4.0 at baseline to 2.7 at week 12 with the therapy combination; at week 16, the mean WI-NRS score fell further to 1.8.

A total of 6 AEs were reported in 5 (16.7%) patients (Table 2). The majority (4/6 [67.0%]) of AEs were considered mild. Two reported cases of COVID-19 were both considered mild and unrelated. Mild folliculitis and moderate worsening of psoriasis in 2 (6.7%) different patients were the only AEs considered related to treatment. No serious AEs were reported, and no patient withdrew from the study due to an AE.

Comment

In this prospective, open-label, real-world study, we found that when a patient’s response to a biologic is unsatisfactory, adding nonsteroidal tapinarof cream can enhance the treatment effect of the biologic. More than half of patients who were not adequately responding to a biologic reached the TTT goal at week 12, which was maintained in most of the responders for 4 weeks after tapinarof discontinuation. All measures of disease activity and quality of life (measured by the DLQI) improved when tapinarof was introduced, and the combination was well tolerated and without any unexpected safety signals.

Disease activity improvements we observed with the nonsteroidal tapinarof cream were consistent with those reported when topical steroidal therapies were given to patients responding poorly to their current biologic. Our primary end point (proportion of patients with BSA involvement ≤1% after 12 weeks) showed that half (52% [11/21]) of patients whose BSA involvement was 3% or greater with a biologic for 24 weeks or more reached the TTT goal after 12 weeks of tapinarof-biologic treatment. Other studies of halobetasol propionate–tazarotene lotion¹⁶ and calcipotriene/betamethasone dipropionate foam^17,18 added to the current biologic of poor responders found 60% to 68% of patients had reductions in their percentage BSA to 1% or lower at 12 to 16 weeks of treatment. Randomized studies showed etanercept plus topical clobetasol propionate foam²⁰ or adalimumab plus calcipotriene/betamethasone dipropionate foam²¹ similarly enhanced treatment effects vs biologic alone.

A phase 3 PSOARING trial demonstrated benefit from treatment with tapinarof alone, with a remittive effect of approximately 4 months after discontinuation.²⁵ Our data are consistent with these findings, with 40% (8/20) of patients demonstrating a remittive effect 4 weeks after discontinuing tapinarof while receiving a biologic. A similar maintenance effect was reported in another study in 50% (9/18) of patients treated with a biologic plus halobetasol propionate–tazarotene lotion.¹⁶ Additionally, when halcinonide ointment was given to patients receiving tildrakizumab, mean percentage of BSA involvement, PGA scores, PGA×BSA, and DLQI scores improved and were maintained 4 weeks after halcinonide ointment was stopped.¹⁹ Thus, topical therapy can augment and extend a biologic’s effect for up to 4 weeks. While a longer remittive effect is possible in our patients based on the 4-month remittive rate observed in the PSOARING trials,²⁵ further patient observation would be needed to confirm.

In our study, tapinarof cream added to a biologic had a good safety and tolerability profile. Few AEs were recorded, with most being mild in nature, and no serious AEs or discontinuations due to AEs were reported. Only 1 case of mild folliculitis and 1 case of moderate worsening of psoriasis were considered treatment related. Further, no unexpected or new safety signals with the tapinarof-biologic combination were observed compared with tapinarof alone.²⁷Prior studies have found that supplementing a biologic with topical therapy can reduce the probability of patients switching to another biologic.^16,19 We previously found that adding halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam¹⁷ to a biologic helped reduce the probability of switching biologics from 88% to 90% at baseline to 12% to 24% after 12 weeks of combined therapy. Such combinations also could prevent a less responsive patient from being prescribed a higher biologic dose.¹⁹ These are important research findings, as patients—even when not responding well to their current biologic—are more likely to be tolerating that biologic well, and switching to a new biologic may introduce new safety or tolerability concerns. Thus, by enhancing the effect of a biologic with a topical therapy, one can avoid increasing the dose of the current biologic or switching to a new biologic, either of which may increase safety and/or tolerability risks. Switching biologics also has increased cost implications to the health care system and/or the patient. When comparing the cost of adding halobetasol propionate–tazarotene lotion to a biologic compared with switching to another biologic, the cost was 1.2 to 2.9 times higher to switch, depending on the biologic, compared with a smaller incremental cost increase to add a topical to the current biologic.¹⁶ Similar observations were reported with calcipotriene/betamethasone dipropionate foam plus a biologic.¹⁷ Although we did not evaluate biologic switching here, we anticipate a similar clinical scenario with a tapinarof-biologic combination.

Limitations of our study included the open-label design, lack of a control arm, and the relatively small study population; however, for studies investigating the safety and effectiveness of a treatment in a real-world setting, these limitations are common and are not unexpected. Our results also are consistent with the overall improvement seen in other studies^16-21 examining the effects of adding a topical to a biologic. Future research is warranted to investigate a longer remittive effect and potential health care system and patient cost savings without having to switch biologics due to lack of effectiveness.

Conclusion

This study demonstrated that adjunctive use of nonsteroidal tapinarof cream 1% may enhance a biologic treatment effect in patients with moderate to severe plaque psoriasis, providing an adequate response for many patients who were not responding well to a biologic alone. Clinical outcomes improved with the tapinarof-biologic combination, and a remittive effect was noted 4 weeks after tapinarof discontinuation without any new safety signals. Adding tapinarof cream to a biologic also may prevent the need to switch biologics when patients do not sufficiently respond, preserving the safety and cost associated with a patient’s current biologic.

The estimated prevalence of psoriasis in individuals older than 20 years in the United States has been reported at approximately 3%, or more than 7.5 million people.¹ There currently is no cure for psoriasis, and available therapeutics, including phototherapy,² topical therapies,³ systemic medications,⁴ and biologic agents,⁵ are focused only on controlling symptoms. The National Psoriasis Foundation defines an acceptable treatment response for plaque psoriasis as 3% or lower body surface area (BSA) involvement after 3 months of therapy, with a treat-to-target (TTT) goal of 1% or less BSA involvement.⁶

Cytokines are known to mediate psoriasis pathology, and biologic therapies target the signaling cascade of various cytokines. Biologics approved to treat moderate to severe plaque psoriasis include IgG monoclonal antibodies binding and inhibiting the activity of interleukin (IL)-17 (ixekizumab,⁷ secukinumab⁸), IL-23 (guselkumab,⁹ risankizumab,¹⁰ tildrakizumab¹¹), and IL-12/23 (ustekinumab¹²). Despite targeting these cytokines, biologics may not sufficiently suppress the symptoms of psoriatic disease and their severity in all patients. Adding a topical treatment to biologic therapy can augment clinical response without increasing the incidence of adverse effects^13-15 and may reduce the need to switch biologics due to ineffectiveness. Switching biologics likely would increase cost burden to the health care system and/or patient depending on their insurance plan and possibly introduce new safety and/or tolerability issues.^16,17

In patients who do not adequately respond to biologics, better responses were reported when topical medications including halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam^17,18 were administered. In randomized or open-label, real-world studies, patients with psoriasis responded well when topical medications were added to a biologic, such as tildrakizumab combined with halcinonide ointment 0.1%,¹⁹ etanercept combined with topical clobetasol propionate foam,²⁰ or adalimumab combined with calcipotriene/betamethasone dipropionate foam.²¹ No additional safety concerns were observed with the topical add-ons in any of these studies.

Tapinarof is an aryl hydrocarbon receptor agonist approved by the US Food and Drug Administration for topical treatment of plaque psoriasis in adults.²² It is a first-in-class small molecule with a novel mechanism of action that downregulates IL-17A and IL-17F and normalizes the skin barrier through expression of filaggrin, loricrin, and involucrin; it also has antioxidant activity.²³ In the phase 3 PSOARING 1 and 2 trials, daily application of tapinarof cream was safe and efficacious in patients with plaque psoriasis,^24,25 with a remittive (maintenance) effect of a median of approximately 4 months after discontinuation.²⁵ In these 2 phase 3 studies, tapinarof significantly (P<0.01 at week 12) relieved itch, which was seen rapidly (P<0.05 at week 2),²⁶ improved quality of life,²⁷ and led to high patient satisfaction.²⁷ When tapinarof cream was combined with deucravacitinib in a patient with severe plaque psoriasis, symptoms rapidly cleared, with a 75% decrease in disease severity after 4 weeks.²⁸

The objective of this prospective, open-label, real-world, single-center study was to assess the effectiveness, safety, and remittive (or maintenance) effect of nonsteroidal tapinarof cream 1% added to ongoing biologic therapy in patients with plaque psoriasis who were not adequately responding to a biologic alone.

Methods

Study Design and Participants—This prospective, open-label, real-world, single-center study assessed the safety and effectiveness of once-daily application of tapinarof cream 1% added to ongoing biologic therapy to help reach the National Psoriasis Foundation’s TTT goal of 1% or less BSA involvement at week 12 in patients with 3% or greater BSA involvement after taking the biologic for 24 weeks or more. The study protocol was approved by an institutional review board, and the study was conducted according to the ethical guidelines of the Declaration of Helsinki and Good Clinical Practice. All participants provided written informed consent before the study began.

Eligible participants were otherwise healthy males and females aged 18 years and older with moderate to severe plaque psoriasis (BSA involvement ≥3%) who had been treated with a biologic for 24 weeks or more. Patients were recruited from the Psoriasis Treatment Center of New Jersey (East Windsor, New Jersey). Exclusion criteria were recent use of oral systemic therapies (within 4 weeks of baseline) or topical therapies (within 2 weeks) to treat psoriasis, recent use of UVB (within 2 weeks) or psoralen plus UVA (within 4 weeks) phototherapy, or use of any investigational drug within 4 weeks of baseline (or within 5 pharmacokinetic/pharmacodynamic half-lives, whichever was longer). Patients who were pregnant or breastfeeding or who had any known hypersensitivity to the excipients of tapinarof cream also were excluded from the study.

Eligible participants received tapinarof cream 1% once daily plus their ongoing biologic for 12 weeks, after which tapinarof was discontinued and the biologic was continued for an additional 4 weeks. A remittive (maintenance) effect was assessed at week 16.

Study Outcomes—Safety and efficacy were evaluated at baseline and weeks 2, 4, 8, 12, and 16. The primary end point was the proportion of patients who reached the TTT goal of 1% or less BSA involvement at week 12. Secondary end points included the proportion of patients with 1% or less BSA involvement at weeks 2, 4, 8, and 16; and PGA scores, composite PGA multiplied by mean percentage of BSA involvement (PGA×BSA), and PASI scores at baseline and weeks 2, 4, 8, 12, and 16. The patient-reported outcomes of Dermatology Life Quality Index (DLQI) and Worst Itch Numeric Rating Scale (WI-NRS) scores also were evaluated at baseline and weeks 2, 4, 8, 12, and 16. In patients who had disease involvement on the scalp or genital region at baseline, Psoriasis Scalp Severity Index (PSSI) and Static Physician’s Global Assessment of Genitalia scores, respectively, were assessed at baseline and weeks 2, 4, 8, 12, and 16. Safety was determined by the incidence, severity, and relatedness of adverse events (AEs) and serious AEs.

Statistical Analysis—Approximately 30 participants were planned for enrollment and recruited consecutively as they were identified during screening against inclusion and exclusion criteria. Changes from baseline in all outcomes were summarized descriptively. Missing data were not imputed. Given the sample size, no formal statistical analyses were conducted. Safety was summarized by descriptively collating AEs and serious AEs, including their frequency, severity, and treatment relatedness.

Results

Thirty participants were enrolled in the study, and 20 fully completed the study. Nine discontinued treatment before week 12 (6 were lost to follow-up, 2 were terminated early by the investigators, and 1 voluntarily withdrew); 1 additional participant was lost to follow-up after week 12. Patients were predominantly male (20/30 [66.7%]) and White (21/30 [70.0%]); the mean age of all participants was 55.4 years, and the mean (SD) duration of psoriasis was 21.4 (15.0) years (Table 1). The mean baseline percentage of BSA involvement and mean baseline PGA, PASI, and DLQI scores are shown in Table 1. Most (19/30 [63.3%]) patients received biologics that inhibited IL-23 activity (guselkumab, risankizumab, tildrakizumab), approximately one-third (9/30 [30.0%]) received biologics that inhibited IL-17 activity (ixekizumab, secukinumab), and 2 (6.7%) received biologics that inhibited IL-12/IL-23 activity (ustekinumab)(Table 1).

For the primary end point, 52.4% (11/21) of patients reached the TTT goal (BSA involvement ≤1% after 12 weeks of treatment with tapinarof cream added to a prescribed biologic). The proportion of patients reaching the TTT goal increased over time with the combined treatment (eFigure 1). Additionally, the mean percentage of BSA involvement (eFigure 2) as well as the mean values for PGA (eFigure 3) and PGA×BSA decreased over time. The mean percentage of BSA involvement was 5.0% at baseline and dropped to 2.0% by week 12. Similar reductions were observed for PGA and PGA×BSA scores at week 12.

After discontinuing tapinarof cream at week 12 and receiving only the biologic for 4 weeks, the proportion of patients maintaining 1% or less BSA involvement fell to 40.0% (8/20) at week 16, which was closer to that observed at week 8 (36% [9/25]) than at week 12 (52.4% [11/21])(eFigure 1).

The mean PASI score was 5.5 at baseline, then decreased over time when tapinarof cream was combined with a biologic (eFigure 4), falling to 3.1 by week 2 and 1.6 by week 12; it was maintained at 1.7 at week 16. Nine (30.0%) participants had psoriasis on the scalp at baseline with a mean PSSI score of 2.6, which decreased to 0.83 by week 2. By week 12, the mean PSSI score remained stable at 0.95 in the 2 (9.5%) participants who still had scalp involvement. The mean PSSI score increased slightly to 1.45 after patients received only the biologic for 4 weeks. At baseline, 3 (10.0%) patients had genital involvement (mean Static Physician’s Global Assessment of Genitalia score, 0.27). Symptoms resolved in 2 (66.7%) of these patients at week 2 and stayed consistent until week 16; the third patient withdrew at week 2.

Both DLQI and WI-NRS scores decreased with use of tapinarof cream added to a biologic up to week 12 (eFigures 5 and 6). Mean DLQI scores were 5.3 at baseline and 3.1 at week 12. At week 16, the mean DLQI score remained stable at 2.8. Mean WI-NRS scores decreased from 4.0 at baseline to 2.7 at week 12 with the therapy combination; at week 16, the mean WI-NRS score fell further to 1.8.

A total of 6 AEs were reported in 5 (16.7%) patients (Table 2). The majority (4/6 [67.0%]) of AEs were considered mild. Two reported cases of COVID-19 were both considered mild and unrelated. Mild folliculitis and moderate worsening of psoriasis in 2 (6.7%) different patients were the only AEs considered related to treatment. No serious AEs were reported, and no patient withdrew from the study due to an AE.

Comment

In this prospective, open-label, real-world study, we found that when a patient’s response to a biologic is unsatisfactory, adding nonsteroidal tapinarof cream can enhance the treatment effect of the biologic. More than half of patients who were not adequately responding to a biologic reached the TTT goal at week 12, which was maintained in most of the responders for 4 weeks after tapinarof discontinuation. All measures of disease activity and quality of life (measured by the DLQI) improved when tapinarof was introduced, and the combination was well tolerated and without any unexpected safety signals.

Disease activity improvements we observed with the nonsteroidal tapinarof cream were consistent with those reported when topical steroidal therapies were given to patients responding poorly to their current biologic. Our primary end point (proportion of patients with BSA involvement ≤1% after 12 weeks) showed that half (52% [11/21]) of patients whose BSA involvement was 3% or greater with a biologic for 24 weeks or more reached the TTT goal after 12 weeks of tapinarof-biologic treatment. Other studies of halobetasol propionate–tazarotene lotion¹⁶ and calcipotriene/betamethasone dipropionate foam^17,18 added to the current biologic of poor responders found 60% to 68% of patients had reductions in their percentage BSA to 1% or lower at 12 to 16 weeks of treatment. Randomized studies showed etanercept plus topical clobetasol propionate foam²⁰ or adalimumab plus calcipotriene/betamethasone dipropionate foam²¹ similarly enhanced treatment effects vs biologic alone.

A phase 3 PSOARING trial demonstrated benefit from treatment with tapinarof alone, with a remittive effect of approximately 4 months after discontinuation.²⁵ Our data are consistent with these findings, with 40% (8/20) of patients demonstrating a remittive effect 4 weeks after discontinuing tapinarof while receiving a biologic. A similar maintenance effect was reported in another study in 50% (9/18) of patients treated with a biologic plus halobetasol propionate–tazarotene lotion.¹⁶ Additionally, when halcinonide ointment was given to patients receiving tildrakizumab, mean percentage of BSA involvement, PGA scores, PGA×BSA, and DLQI scores improved and were maintained 4 weeks after halcinonide ointment was stopped.¹⁹ Thus, topical therapy can augment and extend a biologic’s effect for up to 4 weeks. While a longer remittive effect is possible in our patients based on the 4-month remittive rate observed in the PSOARING trials,²⁵ further patient observation would be needed to confirm.

In our study, tapinarof cream added to a biologic had a good safety and tolerability profile. Few AEs were recorded, with most being mild in nature, and no serious AEs or discontinuations due to AEs were reported. Only 1 case of mild folliculitis and 1 case of moderate worsening of psoriasis were considered treatment related. Further, no unexpected or new safety signals with the tapinarof-biologic combination were observed compared with tapinarof alone.²⁷Prior studies have found that supplementing a biologic with topical therapy can reduce the probability of patients switching to another biologic.^16,19 We previously found that adding halobetasol propionate–tazarotene lotion¹⁶ or calcipotriene/betamethasone dipropionate foam¹⁷ to a biologic helped reduce the probability of switching biologics from 88% to 90% at baseline to 12% to 24% after 12 weeks of combined therapy. Such combinations also could prevent a less responsive patient from being prescribed a higher biologic dose.¹⁹ These are important research findings, as patients—even when not responding well to their current biologic—are more likely to be tolerating that biologic well, and switching to a new biologic may introduce new safety or tolerability concerns. Thus, by enhancing the effect of a biologic with a topical therapy, one can avoid increasing the dose of the current biologic or switching to a new biologic, either of which may increase safety and/or tolerability risks. Switching biologics also has increased cost implications to the health care system and/or the patient. When comparing the cost of adding halobetasol propionate–tazarotene lotion to a biologic compared with switching to another biologic, the cost was 1.2 to 2.9 times higher to switch, depending on the biologic, compared with a smaller incremental cost increase to add a topical to the current biologic.¹⁶ Similar observations were reported with calcipotriene/betamethasone dipropionate foam plus a biologic.¹⁷ Although we did not evaluate biologic switching here, we anticipate a similar clinical scenario with a tapinarof-biologic combination.

Limitations of our study included the open-label design, lack of a control arm, and the relatively small study population; however, for studies investigating the safety and effectiveness of a treatment in a real-world setting, these limitations are common and are not unexpected. Our results also are consistent with the overall improvement seen in other studies^16-21 examining the effects of adding a topical to a biologic. Future research is warranted to investigate a longer remittive effect and potential health care system and patient cost savings without having to switch biologics due to lack of effectiveness.

Conclusion

This study demonstrated that adjunctive use of nonsteroidal tapinarof cream 1% may enhance a biologic treatment effect in patients with moderate to severe plaque psoriasis, providing an adequate response for many patients who were not responding well to a biologic alone. Clinical outcomes improved with the tapinarof-biologic combination, and a remittive effect was noted 4 weeks after tapinarof discontinuation without any new safety signals. Adding tapinarof cream to a biologic also may prevent the need to switch biologics when patients do not sufficiently respond, preserving the safety and cost associated with a patient’s current biologic.

Psoriasis, one of the most researched diseases in dermatology, has a complex pathogenesis that is not yet fully understood. One of the most important stages of psoriasis pathogenesis is the proliferation of T helper (Th) 17 cells by IL-23 released from myeloid dendritic cells. Cytokines such as tumor necrosis factor (TNF) α released from Th1 cells and IL-17 and IL-22 released from Th17 cells are known to induce the proliferation of keratinocytes and the release of chemokines responsible for neutrophil chemotaxis.¹

Although secondary messengers such as cytokines and chemokines, which provide cell interaction with the extracellular matrix (ECM), have their own specific receptors, it is known that syndecans (SDCs) play a role in ECM and cell interactions and have receptor or coreceptor functions.² In humans, 4 types of SDCs have been identified (SDC1-SDC4), which are type I transmembrane proteoglycans found in all nucleated cells. Syndecans consist of heparan sulfate glycosaminoglycan chains that are structurally linked to a core protein sequence. The molecule has cytoplasmic, transmembrane, and extracellular domains.^2,3 While SDCs often are described as coreceptors for integrins and growth factor and hormone receptors, they also are capable of acting as signaling receptors by engaging intracellular messengers, including actin-related proteins and protein kinases.⁴ 

Prior research has indicated that the release of heparanase from the lysosomes of leukocytes during infection, inflammation, and endothelial damage causes cleavage of heparan sulfate glycosaminoglycans from the extracellular domains of SDCs. The peptide chains at the SDC core then are separated by matrix metalloproteinases in a process known as shedding. The shed SDCs may have either a stimulating or a suppressive effect on their receptor activity. Several cytokines are known to cause SDC shedding.^5,6 Many studies in recent years have reported that SDCs play a role in the pathogenesis of inflammatory diseases, for which serum levels of soluble SDCs can be biomarkers.⁷

In this study, we aimed to evaluate and compare serum SDC1, SDC4, TNF-α, and IL-17A levels in patients with psoriasis vs healthy controls. Additionally, by reviewing the literature data, we analyzed whether SDCs can be implicated in the pathogenesis of psoriasis and their potential role in this process.

Methods

The study population consisted of 40 patients with psoriasis and 40 healthy controls. Age and sex characteristics were similar between the 2 groups, but weight distribution was not. The psoriasis group included patients older than 18 years who had received a clinical and/or ­histologic diagnosis, had no systemic disease other than psoriasis in their medical history, and had not used any systemic treatment or phototherapy for the past 3 months. Healthy patients older than 18 years who had no medical history of inflammatory disease were included in the control group. Participants provided signed consent.

Data such as medical history, laboratory findings, and physical specifications were recorded. A Psoriasis Area and Severity Index (PASI) score of 10 or lower was considered mild disease, and a score higher than 10 was considered moderate to severe disease. An enzyme-linked immunosorbent assay was used to measure SDC1, SDC4, TNF-α, and IL-17A levels. 

The data were evaluated using the IBM SPSS Statistics V22.0 statistical package program. A P value of <.05 was considered statistically significant. The conformity of the data to a normal distribution was examined using a Shapiro-Wilk test. Normally distributed variables were expressed as mean (SD) and nonnormally distributed variables were expressed as median (interquartile range [IQR]). Data were compared between the 2 study groups using either a student t test (normal distribution) or Mann-Whitney U test (nonnormal distribution). Categorical variables were expressed as numbers and percentages. Categorical data were compared using a χ² test. Associations among SDC1, SDC4, TNF-α, IL-17A, and other variables were assessed using Spearman rank correlation. A binary logistic regression analysis was used to determine whether serum SDC1 and SDC4 levels were independent risk factors for psoriasis.

Results

The 2 study groups showed similar demographic characteristics in terms of sex (P=.67) and age (P=.22) distribution. The mean (SD) PASI score in the psoriasis group was 12.33 (7.62); the mean (SD) disease duration was 11.10 (8.00) years. Body weight and BMI were both significantly higher in the psoriasis group (P=.027 and P=.029, respectively) compared with the control group (eTable 1).

The mean (SD) serum SDC1 level was 119.52 ng/mL (69.53 ng/mL) in the psoriasis group, which was significantly higher than the control group (82.81 ng/mL [51.85 ng/mL])(P=.011)(eTable 2)(eFigure 1). The median (IQR) serum SDC4 level also was significantly higher in the psoriasis group compared with the control group (5.78 ng/mL [7.09 ng/mL] vs 3.92 ng/mL [2.88 ng/mL])(P=.030)(eTable 2)(eFigure 2). The median (IQR) IL-17A value was 59.94 pg/mL (12.97 pg/mL) in the psoriasis group, which was significantly higher than the control group (37.74 pg/mL [15.10 pg/mL])(P<.001)(eTable 2)(eFigure 3). The median (IQR) serum TNF-α level was 25.07 pg/mL (41.70 pg/mL) in the psoriasis group and 18.21 pg/mL (48.51 pg/mL) in the control group; however, the difference was not statistically significance (P=.444)(eTable 2)(eFigure 4). 

A significant positive correlation was found between serum SDC1 and PASI score (p=0.064; P=.03). Furthermore, significant positive correlations were ­identified between serum SDC1 and body weight (p=0.404; P<.001), disease duration (p=0.377; P=.008), and C-reactive protein (p=0.327; P=.002). A significant positive correlation also was identified between SDC4 and IL-17A (p=0.265; P=.009). Serum TNF-α was positively correlated with IL-17A (p=0.384; P<.001) and BMI (p=0.234; P=.020)(eTable 3).

Logistic regression analysis showed that high SDC1 levels were independently associated with the development of psoriasis (odds ratio [OR], 1.009; 95% CI, 1.000-1.017; P=.049)(eTable 4).

Comment

Tumor necrosis factor α and IL-17A are key cytokines whose roles in the pathogenesis of psoriasis are well established. Arican et al,⁸ Kyriakou et al,⁹ and Xuan et al¹⁰ previously reported a lack of any correlation between TNF-α and IL-17A in the pathogenesis of psoriasis; however, we observed a positive correlation between TNF-α and IL-17A in our study. This finding may be due to the abundant TNF-α production by myeloid dendritic cells involved in the transformation of naive T lymphocytes into IL-17A–secreting Th17 lymphocytes, which can also secrete TNF-α.

After the molecular cloning of SDCs by Saunders et al¹¹ in 1989, SDCs gained attention and have been the focus of many studies for their part in the pathogenesis of conditions such as inflammatory diseases, carcinogenesis, infections, sepsis, and trauma.^6,12 Among the inflammatory diseases sharing similar pathogenetic features to psoriasis, serum SDC4 levels are found to be elevated in rheumatoid arthritis and are correlated with disease activity.¹³ Cekic et al¹⁴ reported that serum SDC1 levels were significantly higher in patients with Crohn disease than controls (P=.03). Additionally, serum SDC1 levels were higher in patients with active disease compared with those who were in remission. Correlations between SDC1 and disease severity and C-reactive protein also have been found.¹⁴ Serum SDC-1 levels found to be elevated in patients with systemic lupus erythematosus were compared to the controls and were correlated with disease activity.¹⁵ Nakao et al¹⁶ reported that the serum SDC4 levels were significantly higher in patients with atopic dermatitis compared to controls (P<.01); further, SDC4 levels were correlated with severity of the disease.

Jaiswal et al¹⁷ reported that SDC1 is abundant on the surface of IL-17A–secreting γδ T lymphocytes (Tγδ17), whose contribution to psoriasis pathogenesis is known. When subjected to treatment with imiquimod, SDC1-suppressed mice displayed increased psoriasiform dermatitis compared with wild-type counterparts. The authors stated that SDC1 may play a role in controlling homeostasis of Tγδ17.¹⁷

In a study examining changes in the ECM in patients with psoriasis, it was observed that the expression of heparanase and metalloproteinase enzymes, which are responsible for SDC shedding, was higher in psoriasis plaques vs unaffected skin; furthermore, heparanase, metalloproteinases, and SDC1 expression were higher in unaffected skin samples from patients with psoriasis compared with tissues obtained from individuals without psoriasis.¹⁸ These data support our results, as increased serum SDC levels reflect increased shedding from the cell surface by heparanase and metalloproteinase activity. Pointing to the role of SDC1 in psoriasis, another study reported that upregulation of the metalloproteinase meprin β leads to increased SDC1 shedding; in turn, this shedding leads to impaired adhesion and differentiation of keratinocytes, resulting in psoriasislike skin changes in a mouse model.¹⁹

A study conducted by Koliakou et al²⁰ showed that, in healthy skin, SDC1 was expressed in almost the full thickness of the epidermis, but lowest expression was in the basal-layer keratinocytes. In a psoriatic epidermis, unlike the normal epidermis, SDC1 was found to be more intensely expressed in the keratinocytes of the basal layer, where keratinocyte proliferation occurs. In this study, SDC4 was expressed mainly at lower levels in a healthy epidermis, especially in the spinous and the basal layers. In a psoriatic epidermis, SDC4 was absent from all the layers. In the same study, gelatin-based carriers containing anti–TNF-α and anti–IL-17A were applied to a full-thickness epidermis with psoriatic lesions, after which SDC1 expression was observed to decrease almost completely in the psoriatic epidermis; there was no change in SDC4 expression, which also was not seen in the psoriatic epidermis. The authors claimed the application of these gelatin-based carriers could be a possible treatment modality for psoriasis, and the study provides evidence for the involvement of SDC1 and/or SDC4 in the pathogenesis of psoriasis.²⁰ Supporting these findings, another study showed that phototherapy can reduce SDC1 expression in psoriatic skin.²¹ In our study, a significant positive correlation was found between serum SDC4 and IL-17A (P=.009). IL-17A is known to be the key cytokine that stimulates keratinocyte proliferation in affected skin. Koliakou et al²⁰ reported that SDC4 was present on the surface of keratinocytes in normal skin but not in the psoriatic epidermis. This raises the question if IL-17A might lead to an increase in the shedding of SDC4; thus, SDC4 may mediate the effects of IL-17A.

Limitations of the current study include small sample size, lack of longitudinal data, lack of tissue testing of these molecules, and lack of external validation.

Conclusion

Overall, research has shown that SDCs play important roles in inflammatory processes, and more widespread inflammation has been associated with increased shedding of these molecules into the ECM and higher serum levels. In our study, serum SDC1, SDC4, and IL-17A levels were increased in patients with psoriasis compared to the healthy controls. A logistic regression analysis indicated that high serum SDC1 levels may be an independent risk factor for development of psoriasis. The increase in serum SDC1 and SDC4 levels and the positive correlation between SDC1 levels and disease severity observed in our study strongly implicate SDCs in the inflammatory disease psoriasis. The precise role of SDCs in the pathogenesis of psoriasis and the implications of targeting these molecules are the subject of more in-depth studies in the future.

Psoriasis, one of the most researched diseases in dermatology, has a complex pathogenesis that is not yet fully understood. One of the most important stages of psoriasis pathogenesis is the proliferation of T helper (Th) 17 cells by IL-23 released from myeloid dendritic cells. Cytokines such as tumor necrosis factor (TNF) α released from Th1 cells and IL-17 and IL-22 released from Th17 cells are known to induce the proliferation of keratinocytes and the release of chemokines responsible for neutrophil chemotaxis.¹

Although secondary messengers such as cytokines and chemokines, which provide cell interaction with the extracellular matrix (ECM), have their own specific receptors, it is known that syndecans (SDCs) play a role in ECM and cell interactions and have receptor or coreceptor functions.² In humans, 4 types of SDCs have been identified (SDC1-SDC4), which are type I transmembrane proteoglycans found in all nucleated cells. Syndecans consist of heparan sulfate glycosaminoglycan chains that are structurally linked to a core protein sequence. The molecule has cytoplasmic, transmembrane, and extracellular domains.^2,3 While SDCs often are described as coreceptors for integrins and growth factor and hormone receptors, they also are capable of acting as signaling receptors by engaging intracellular messengers, including actin-related proteins and protein kinases.⁴ 

Prior research has indicated that the release of heparanase from the lysosomes of leukocytes during infection, inflammation, and endothelial damage causes cleavage of heparan sulfate glycosaminoglycans from the extracellular domains of SDCs. The peptide chains at the SDC core then are separated by matrix metalloproteinases in a process known as shedding. The shed SDCs may have either a stimulating or a suppressive effect on their receptor activity. Several cytokines are known to cause SDC shedding.^5,6 Many studies in recent years have reported that SDCs play a role in the pathogenesis of inflammatory diseases, for which serum levels of soluble SDCs can be biomarkers.⁷

In this study, we aimed to evaluate and compare serum SDC1, SDC4, TNF-α, and IL-17A levels in patients with psoriasis vs healthy controls. Additionally, by reviewing the literature data, we analyzed whether SDCs can be implicated in the pathogenesis of psoriasis and their potential role in this process.

Methods

The study population consisted of 40 patients with psoriasis and 40 healthy controls. Age and sex characteristics were similar between the 2 groups, but weight distribution was not. The psoriasis group included patients older than 18 years who had received a clinical and/or ­histologic diagnosis, had no systemic disease other than psoriasis in their medical history, and had not used any systemic treatment or phototherapy for the past 3 months. Healthy patients older than 18 years who had no medical history of inflammatory disease were included in the control group. Participants provided signed consent.

Data such as medical history, laboratory findings, and physical specifications were recorded. A Psoriasis Area and Severity Index (PASI) score of 10 or lower was considered mild disease, and a score higher than 10 was considered moderate to severe disease. An enzyme-linked immunosorbent assay was used to measure SDC1, SDC4, TNF-α, and IL-17A levels. 

The data were evaluated using the IBM SPSS Statistics V22.0 statistical package program. A P value of <.05 was considered statistically significant. The conformity of the data to a normal distribution was examined using a Shapiro-Wilk test. Normally distributed variables were expressed as mean (SD) and nonnormally distributed variables were expressed as median (interquartile range [IQR]). Data were compared between the 2 study groups using either a student t test (normal distribution) or Mann-Whitney U test (nonnormal distribution). Categorical variables were expressed as numbers and percentages. Categorical data were compared using a χ² test. Associations among SDC1, SDC4, TNF-α, IL-17A, and other variables were assessed using Spearman rank correlation. A binary logistic regression analysis was used to determine whether serum SDC1 and SDC4 levels were independent risk factors for psoriasis.

Results

The 2 study groups showed similar demographic characteristics in terms of sex (P=.67) and age (P=.22) distribution. The mean (SD) PASI score in the psoriasis group was 12.33 (7.62); the mean (SD) disease duration was 11.10 (8.00) years. Body weight and BMI were both significantly higher in the psoriasis group (P=.027 and P=.029, respectively) compared with the control group (eTable 1).

The mean (SD) serum SDC1 level was 119.52 ng/mL (69.53 ng/mL) in the psoriasis group, which was significantly higher than the control group (82.81 ng/mL [51.85 ng/mL])(P=.011)(eTable 2)(eFigure 1). The median (IQR) serum SDC4 level also was significantly higher in the psoriasis group compared with the control group (5.78 ng/mL [7.09 ng/mL] vs 3.92 ng/mL [2.88 ng/mL])(P=.030)(eTable 2)(eFigure 2). The median (IQR) IL-17A value was 59.94 pg/mL (12.97 pg/mL) in the psoriasis group, which was significantly higher than the control group (37.74 pg/mL [15.10 pg/mL])(P<.001)(eTable 2)(eFigure 3). The median (IQR) serum TNF-α level was 25.07 pg/mL (41.70 pg/mL) in the psoriasis group and 18.21 pg/mL (48.51 pg/mL) in the control group; however, the difference was not statistically significance (P=.444)(eTable 2)(eFigure 4). 

A significant positive correlation was found between serum SDC1 and PASI score (p=0.064; P=.03). Furthermore, significant positive correlations were ­identified between serum SDC1 and body weight (p=0.404; P<.001), disease duration (p=0.377; P=.008), and C-reactive protein (p=0.327; P=.002). A significant positive correlation also was identified between SDC4 and IL-17A (p=0.265; P=.009). Serum TNF-α was positively correlated with IL-17A (p=0.384; P<.001) and BMI (p=0.234; P=.020)(eTable 3).

Logistic regression analysis showed that high SDC1 levels were independently associated with the development of psoriasis (odds ratio [OR], 1.009; 95% CI, 1.000-1.017; P=.049)(eTable 4).

Comment

Tumor necrosis factor α and IL-17A are key cytokines whose roles in the pathogenesis of psoriasis are well established. Arican et al,⁸ Kyriakou et al,⁹ and Xuan et al¹⁰ previously reported a lack of any correlation between TNF-α and IL-17A in the pathogenesis of psoriasis; however, we observed a positive correlation between TNF-α and IL-17A in our study. This finding may be due to the abundant TNF-α production by myeloid dendritic cells involved in the transformation of naive T lymphocytes into IL-17A–secreting Th17 lymphocytes, which can also secrete TNF-α.

After the molecular cloning of SDCs by Saunders et al¹¹ in 1989, SDCs gained attention and have been the focus of many studies for their part in the pathogenesis of conditions such as inflammatory diseases, carcinogenesis, infections, sepsis, and trauma.^6,12 Among the inflammatory diseases sharing similar pathogenetic features to psoriasis, serum SDC4 levels are found to be elevated in rheumatoid arthritis and are correlated with disease activity.¹³ Cekic et al¹⁴ reported that serum SDC1 levels were significantly higher in patients with Crohn disease than controls (P=.03). Additionally, serum SDC1 levels were higher in patients with active disease compared with those who were in remission. Correlations between SDC1 and disease severity and C-reactive protein also have been found.¹⁴ Serum SDC-1 levels found to be elevated in patients with systemic lupus erythematosus were compared to the controls and were correlated with disease activity.¹⁵ Nakao et al¹⁶ reported that the serum SDC4 levels were significantly higher in patients with atopic dermatitis compared to controls (P<.01); further, SDC4 levels were correlated with severity of the disease.

Jaiswal et al¹⁷ reported that SDC1 is abundant on the surface of IL-17A–secreting γδ T lymphocytes (Tγδ17), whose contribution to psoriasis pathogenesis is known. When subjected to treatment with imiquimod, SDC1-suppressed mice displayed increased psoriasiform dermatitis compared with wild-type counterparts. The authors stated that SDC1 may play a role in controlling homeostasis of Tγδ17.¹⁷

In a study examining changes in the ECM in patients with psoriasis, it was observed that the expression of heparanase and metalloproteinase enzymes, which are responsible for SDC shedding, was higher in psoriasis plaques vs unaffected skin; furthermore, heparanase, metalloproteinases, and SDC1 expression were higher in unaffected skin samples from patients with psoriasis compared with tissues obtained from individuals without psoriasis.¹⁸ These data support our results, as increased serum SDC levels reflect increased shedding from the cell surface by heparanase and metalloproteinase activity. Pointing to the role of SDC1 in psoriasis, another study reported that upregulation of the metalloproteinase meprin β leads to increased SDC1 shedding; in turn, this shedding leads to impaired adhesion and differentiation of keratinocytes, resulting in psoriasislike skin changes in a mouse model.¹⁹

A study conducted by Koliakou et al²⁰ showed that, in healthy skin, SDC1 was expressed in almost the full thickness of the epidermis, but lowest expression was in the basal-layer keratinocytes. In a psoriatic epidermis, unlike the normal epidermis, SDC1 was found to be more intensely expressed in the keratinocytes of the basal layer, where keratinocyte proliferation occurs. In this study, SDC4 was expressed mainly at lower levels in a healthy epidermis, especially in the spinous and the basal layers. In a psoriatic epidermis, SDC4 was absent from all the layers. In the same study, gelatin-based carriers containing anti–TNF-α and anti–IL-17A were applied to a full-thickness epidermis with psoriatic lesions, after which SDC1 expression was observed to decrease almost completely in the psoriatic epidermis; there was no change in SDC4 expression, which also was not seen in the psoriatic epidermis. The authors claimed the application of these gelatin-based carriers could be a possible treatment modality for psoriasis, and the study provides evidence for the involvement of SDC1 and/or SDC4 in the pathogenesis of psoriasis.²⁰ Supporting these findings, another study showed that phototherapy can reduce SDC1 expression in psoriatic skin.²¹ In our study, a significant positive correlation was found between serum SDC4 and IL-17A (P=.009). IL-17A is known to be the key cytokine that stimulates keratinocyte proliferation in affected skin. Koliakou et al²⁰ reported that SDC4 was present on the surface of keratinocytes in normal skin but not in the psoriatic epidermis. This raises the question if IL-17A might lead to an increase in the shedding of SDC4; thus, SDC4 may mediate the effects of IL-17A.

Limitations of the current study include small sample size, lack of longitudinal data, lack of tissue testing of these molecules, and lack of external validation.

Conclusion

Overall, research has shown that SDCs play important roles in inflammatory processes, and more widespread inflammation has been associated with increased shedding of these molecules into the ECM and higher serum levels. In our study, serum SDC1, SDC4, and IL-17A levels were increased in patients with psoriasis compared to the healthy controls. A logistic regression analysis indicated that high serum SDC1 levels may be an independent risk factor for development of psoriasis. The increase in serum SDC1 and SDC4 levels and the positive correlation between SDC1 levels and disease severity observed in our study strongly implicate SDCs in the inflammatory disease psoriasis. The precise role of SDCs in the pathogenesis of psoriasis and the implications of targeting these molecules are the subject of more in-depth studies in the future.

Psoriasis, one of the most researched diseases in dermatology, has a complex pathogenesis that is not yet fully understood. One of the most important stages of psoriasis pathogenesis is the proliferation of T helper (Th) 17 cells by IL-23 released from myeloid dendritic cells. Cytokines such as tumor necrosis factor (TNF) α released from Th1 cells and IL-17 and IL-22 released from Th17 cells are known to induce the proliferation of keratinocytes and the release of chemokines responsible for neutrophil chemotaxis.¹

Although secondary messengers such as cytokines and chemokines, which provide cell interaction with the extracellular matrix (ECM), have their own specific receptors, it is known that syndecans (SDCs) play a role in ECM and cell interactions and have receptor or coreceptor functions.² In humans, 4 types of SDCs have been identified (SDC1-SDC4), which are type I transmembrane proteoglycans found in all nucleated cells. Syndecans consist of heparan sulfate glycosaminoglycan chains that are structurally linked to a core protein sequence. The molecule has cytoplasmic, transmembrane, and extracellular domains.^2,3 While SDCs often are described as coreceptors for integrins and growth factor and hormone receptors, they also are capable of acting as signaling receptors by engaging intracellular messengers, including actin-related proteins and protein kinases.⁴ 

Prior research has indicated that the release of heparanase from the lysosomes of leukocytes during infection, inflammation, and endothelial damage causes cleavage of heparan sulfate glycosaminoglycans from the extracellular domains of SDCs. The peptide chains at the SDC core then are separated by matrix metalloproteinases in a process known as shedding. The shed SDCs may have either a stimulating or a suppressive effect on their receptor activity. Several cytokines are known to cause SDC shedding.^5,6 Many studies in recent years have reported that SDCs play a role in the pathogenesis of inflammatory diseases, for which serum levels of soluble SDCs can be biomarkers.⁷

In this study, we aimed to evaluate and compare serum SDC1, SDC4, TNF-α, and IL-17A levels in patients with psoriasis vs healthy controls. Additionally, by reviewing the literature data, we analyzed whether SDCs can be implicated in the pathogenesis of psoriasis and their potential role in this process.

Methods

The study population consisted of 40 patients with psoriasis and 40 healthy controls. Age and sex characteristics were similar between the 2 groups, but weight distribution was not. The psoriasis group included patients older than 18 years who had received a clinical and/or ­histologic diagnosis, had no systemic disease other than psoriasis in their medical history, and had not used any systemic treatment or phototherapy for the past 3 months. Healthy patients older than 18 years who had no medical history of inflammatory disease were included in the control group. Participants provided signed consent.

Data such as medical history, laboratory findings, and physical specifications were recorded. A Psoriasis Area and Severity Index (PASI) score of 10 or lower was considered mild disease, and a score higher than 10 was considered moderate to severe disease. An enzyme-linked immunosorbent assay was used to measure SDC1, SDC4, TNF-α, and IL-17A levels. 

The data were evaluated using the IBM SPSS Statistics V22.0 statistical package program. A P value of <.05 was considered statistically significant. The conformity of the data to a normal distribution was examined using a Shapiro-Wilk test. Normally distributed variables were expressed as mean (SD) and nonnormally distributed variables were expressed as median (interquartile range [IQR]). Data were compared between the 2 study groups using either a student t test (normal distribution) or Mann-Whitney U test (nonnormal distribution). Categorical variables were expressed as numbers and percentages. Categorical data were compared using a χ² test. Associations among SDC1, SDC4, TNF-α, IL-17A, and other variables were assessed using Spearman rank correlation. A binary logistic regression analysis was used to determine whether serum SDC1 and SDC4 levels were independent risk factors for psoriasis.

Results

The 2 study groups showed similar demographic characteristics in terms of sex (P=.67) and age (P=.22) distribution. The mean (SD) PASI score in the psoriasis group was 12.33 (7.62); the mean (SD) disease duration was 11.10 (8.00) years. Body weight and BMI were both significantly higher in the psoriasis group (P=.027 and P=.029, respectively) compared with the control group (eTable 1).

The mean (SD) serum SDC1 level was 119.52 ng/mL (69.53 ng/mL) in the psoriasis group, which was significantly higher than the control group (82.81 ng/mL [51.85 ng/mL])(P=.011)(eTable 2)(eFigure 1). The median (IQR) serum SDC4 level also was significantly higher in the psoriasis group compared with the control group (5.78 ng/mL [7.09 ng/mL] vs 3.92 ng/mL [2.88 ng/mL])(P=.030)(eTable 2)(eFigure 2). The median (IQR) IL-17A value was 59.94 pg/mL (12.97 pg/mL) in the psoriasis group, which was significantly higher than the control group (37.74 pg/mL [15.10 pg/mL])(P<.001)(eTable 2)(eFigure 3). The median (IQR) serum TNF-α level was 25.07 pg/mL (41.70 pg/mL) in the psoriasis group and 18.21 pg/mL (48.51 pg/mL) in the control group; however, the difference was not statistically significance (P=.444)(eTable 2)(eFigure 4). 

A significant positive correlation was found between serum SDC1 and PASI score (p=0.064; P=.03). Furthermore, significant positive correlations were ­identified between serum SDC1 and body weight (p=0.404; P<.001), disease duration (p=0.377; P=.008), and C-reactive protein (p=0.327; P=.002). A significant positive correlation also was identified between SDC4 and IL-17A (p=0.265; P=.009). Serum TNF-α was positively correlated with IL-17A (p=0.384; P<.001) and BMI (p=0.234; P=.020)(eTable 3).

Logistic regression analysis showed that high SDC1 levels were independently associated with the development of psoriasis (odds ratio [OR], 1.009; 95% CI, 1.000-1.017; P=.049)(eTable 4).

Comment

Tumor necrosis factor α and IL-17A are key cytokines whose roles in the pathogenesis of psoriasis are well established. Arican et al,⁸ Kyriakou et al,⁹ and Xuan et al¹⁰ previously reported a lack of any correlation between TNF-α and IL-17A in the pathogenesis of psoriasis; however, we observed a positive correlation between TNF-α and IL-17A in our study. This finding may be due to the abundant TNF-α production by myeloid dendritic cells involved in the transformation of naive T lymphocytes into IL-17A–secreting Th17 lymphocytes, which can also secrete TNF-α.

After the molecular cloning of SDCs by Saunders et al¹¹ in 1989, SDCs gained attention and have been the focus of many studies for their part in the pathogenesis of conditions such as inflammatory diseases, carcinogenesis, infections, sepsis, and trauma.^6,12 Among the inflammatory diseases sharing similar pathogenetic features to psoriasis, serum SDC4 levels are found to be elevated in rheumatoid arthritis and are correlated with disease activity.¹³ Cekic et al¹⁴ reported that serum SDC1 levels were significantly higher in patients with Crohn disease than controls (P=.03). Additionally, serum SDC1 levels were higher in patients with active disease compared with those who were in remission. Correlations between SDC1 and disease severity and C-reactive protein also have been found.¹⁴ Serum SDC-1 levels found to be elevated in patients with systemic lupus erythematosus were compared to the controls and were correlated with disease activity.¹⁵ Nakao et al¹⁶ reported that the serum SDC4 levels were significantly higher in patients with atopic dermatitis compared to controls (P<.01); further, SDC4 levels were correlated with severity of the disease.

Jaiswal et al¹⁷ reported that SDC1 is abundant on the surface of IL-17A–secreting γδ T lymphocytes (Tγδ17), whose contribution to psoriasis pathogenesis is known. When subjected to treatment with imiquimod, SDC1-suppressed mice displayed increased psoriasiform dermatitis compared with wild-type counterparts. The authors stated that SDC1 may play a role in controlling homeostasis of Tγδ17.¹⁷

In a study examining changes in the ECM in patients with psoriasis, it was observed that the expression of heparanase and metalloproteinase enzymes, which are responsible for SDC shedding, was higher in psoriasis plaques vs unaffected skin; furthermore, heparanase, metalloproteinases, and SDC1 expression were higher in unaffected skin samples from patients with psoriasis compared with tissues obtained from individuals without psoriasis.¹⁸ These data support our results, as increased serum SDC levels reflect increased shedding from the cell surface by heparanase and metalloproteinase activity. Pointing to the role of SDC1 in psoriasis, another study reported that upregulation of the metalloproteinase meprin β leads to increased SDC1 shedding; in turn, this shedding leads to impaired adhesion and differentiation of keratinocytes, resulting in psoriasislike skin changes in a mouse model.¹⁹

A study conducted by Koliakou et al²⁰ showed that, in healthy skin, SDC1 was expressed in almost the full thickness of the epidermis, but lowest expression was in the basal-layer keratinocytes. In a psoriatic epidermis, unlike the normal epidermis, SDC1 was found to be more intensely expressed in the keratinocytes of the basal layer, where keratinocyte proliferation occurs. In this study, SDC4 was expressed mainly at lower levels in a healthy epidermis, especially in the spinous and the basal layers. In a psoriatic epidermis, SDC4 was absent from all the layers. In the same study, gelatin-based carriers containing anti–TNF-α and anti–IL-17A were applied to a full-thickness epidermis with psoriatic lesions, after which SDC1 expression was observed to decrease almost completely in the psoriatic epidermis; there was no change in SDC4 expression, which also was not seen in the psoriatic epidermis. The authors claimed the application of these gelatin-based carriers could be a possible treatment modality for psoriasis, and the study provides evidence for the involvement of SDC1 and/or SDC4 in the pathogenesis of psoriasis.²⁰ Supporting these findings, another study showed that phototherapy can reduce SDC1 expression in psoriatic skin.²¹ In our study, a significant positive correlation was found between serum SDC4 and IL-17A (P=.009). IL-17A is known to be the key cytokine that stimulates keratinocyte proliferation in affected skin. Koliakou et al²⁰ reported that SDC4 was present on the surface of keratinocytes in normal skin but not in the psoriatic epidermis. This raises the question if IL-17A might lead to an increase in the shedding of SDC4; thus, SDC4 may mediate the effects of IL-17A.

Limitations of the current study include small sample size, lack of longitudinal data, lack of tissue testing of these molecules, and lack of external validation.

Conclusion

Overall, research has shown that SDCs play important roles in inflammatory processes, and more widespread inflammation has been associated with increased shedding of these molecules into the ECM and higher serum levels. In our study, serum SDC1, SDC4, and IL-17A levels were increased in patients with psoriasis compared to the healthy controls. A logistic regression analysis indicated that high serum SDC1 levels may be an independent risk factor for development of psoriasis. The increase in serum SDC1 and SDC4 levels and the positive correlation between SDC1 levels and disease severity observed in our study strongly implicate SDCs in the inflammatory disease psoriasis. The precise role of SDCs in the pathogenesis of psoriasis and the implications of targeting these molecules are the subject of more in-depth studies in the future.

More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.

More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.

More than 50 million US adults report experiencing chronic pain, with nearly 7% experiencing high-impact chronic pain.^1-3 Chronic pain negatively affects daily function, results in lost productivity, is a leading cause of disability, and is more prevalent among veterans compared with the general population.^1,2,4-6 Estimates from 2021 suggest the prevalence of chronic pain among veterans exceeds 30%; > 11% experienced high-impact chronic pain.¹

Primary care practitioners (PCPs) have a prominent role in chronic pain management. Pharmacologic options for treating pain, once a mainstay of therapy, present several challenges for patients and PCPs, including drug-drug interactions and adverse effects.⁷ The US opioid epidemic and shift to a biopsychosocial model of chronic pain care have increased emphasis on nonpharmacologic treatment options.^8,9 These include integrative modalities, which incorporate conventional approaches with an array of complementary health approaches.^10-12

Integrative therapy is a prominent feature in whole person care, which may be best exemplified by the US Department of Veterans Affairs (VA) Whole Health System of care.^13-14 Whole health empowers an individual to take charge of their health and well-being so they can “live their life to the fullest.”¹⁴ As implemented in the Veterans Health Administration (VHA), whole health includes the use of evidence-based complementary and integrative therapies, encompassing a multimodal pain management approach. Expanding the use of these therapies requires a better understanding of PCP and patient knowledge, interest, and use of integrative modalities for chronic pain.

METHODS

Using a cross-sectional survey design, PCPs and patients with chronic back pain affiliated with the VA Ann Arbor Healthcare System were invited to participate in separate but similar surveys to assess knowledge, interest, and use of nonpharmacologic integrative modalities for the treatment of chronic pain. In May, June, and July 2023, 78 PCPs received 3 email invitations to participate in an electronic (Qualtrics) survey. Patients were identified based on having an International Statistical Classification of Diseases, Tenth Revision code for low back pain (M54.5, M54.40, 41, 42, M54.89) on ≥ 2 outpatient encounters within 18 months (April 1, 2021, to March 31, 2023). A random sample of 200 patients was selected and sent a packet in September 2023 that included an introductory letter and a paper survey, along with a website link and QR code to complete the survey electronically if preferred. The introductory letter stated that participation is voluntary, had no impact on the health care currently received at the VA, and names are not attached to the survey, allowing them to remain anonymous. The packet also included a $10 gift card to encourage survey completion.

Both survey instruments are available upon request, were developed by the study team, and included a mix of yes/no questions, “select all that apply” items, Likert scale response items, and open-ended questions. For one question about which modalities they would like available, the respondent was instructed to select up to 5 modalities. The instruments were extensively pretested by members of the study team, which included 2 PCPs and a nonveteran with chronic back pain.

The list of integrative modalities included in the survey was derived from the tier 1 and tier 2 complementary and integrative health modalities identified in a VHA Directive on complementary and integrative health.^15,16 Tier 1 approaches are considered to have sufficient evidence and must be made available to veterans either within a VA medical facility or in the community. Tier 2 approaches are generally considered safe and may be made available but do not have sufficient evidence to mandate their provision. For participant ease, the integrative modalities were divided into 5 subgroups: manual therapies, energy/biofield therapies, mental health therapies, nutrition counseling, and movement therapies. The clinician survey assessed clinicians’ training and interest, clinical and personal use, and perceived barriers to providing integrative modalities for chronic pain. Professional and personal demographic data were also collected. Similarly, the patient survey assessed use of integrative therapies, perceptions of and interest in integrative modalities, and potential barriers to use. Demographic and health-related information was also collected.

Data analysis included descriptive statistics (eg, frequency counts, means, medians) and visual graphic displays. Separate analyses were conducted for clinicians and patients in addition to a comparative analysis of the use and potential interest in integrative modalities. Analysis were conducted using R software. This study was deemed nonresearch quality improvement by the VA Ann Arbor Healthcare System facility research oversight board and institutional review board approval was not solicited.

RESULTS

Twenty-eight clinicians completed the survey, yielding a participation rate of 36%. Participating clinicians had a median (IQR) age of 48 years (9.5), 15 self-identified as White (54%), 8 as Asian (29%), 15 as female (54%), 26 as non-Hispanic (93%), and 25 were medical doctors or doctors of osteopathy (89%). Nineteen (68%) worked at the main hospital outpatient clinic, and 9 practiced at community-based outpatient clinics (CBOCs). Thirteen respondents (46%) reported having no formal education or training in integrative approaches. Among those with prior training, 8 clinicians had nutrition counseling (29%) and 7 had psychologic therapy training (25%). Thirteen respondents (46%) also reported using integrative modalities for personal health needs: 8 used psychological therapies, 8 used movement therapies, 10 used integrative modalities for stress management or relaxation, and 8 used them for physical symptoms (Table 1).

Overall, 85 of 200 patients (43%) responded to the study survey. Two patients indicated they did not have chronic back pain and were excluded. Patients had a median (IQR) age of 66 (20) years, with 66 self-identifying as White (80%), 69 as male (83%), and 66 as non-Hispanic (80%). Forty-four patients (53%) received care at CBOCs. Forty-seven patients reported excellent, very good, or good overall health (57%), while 53 reported excellent, very good, or good mental health (64%). Fifty-nine patients reported back pain duration > 5 years (71%), and 67 (81%) indicated experiencing back pain flare-ups at least once per week over the previous 12 months. Sixty patients (72%) indicated they were somewhat or very interested in using integrative therapies as a back pain treatment; however, 40 patients (48%) indicated they had not received information about these therapies. Among those who indicated they had received information, the most frequently reported source was their PCP (41%). Most patients (72%) also reported feeling somewhat to very comfortable discussing integrative medicine therapies with their PCP.

Integrative Therapy Recommendations and Use

PCPs reported recommending multiple integrative modalities: 23 (82%) recommended cognitive-behavioral therapy, 22 (79%) recommended acupuncture, 21 (75%) recommended chiropractic, 19 (68%) recommended battlefield acupuncture, recommended massage 18 (64%), 17 (61%) recommended meditation or mindfulness, and 15 (54%) recommended movement therapies such as yoga or tai chi/qigong (Figure 1). The only therapies used by at least half of the patients were chiropractic used by 59 patients (71%) and acupuncture by 42 patients (51%). Thirty-eight patients (46%) reported massage use and 21 patients (25%) used cognitive-behavioral therapy (Table 2).

Integrative Therapies Desired

A majority of PCPs identified acupuncture (n = 20, 71%), chiropractic (n = 19, 68%), and massage (n = 19, 68%) as therapies they would most like to have available for patients with chronic pain (Figure 2). Similarly, patients identified massage (n = 42, 51%), chiropractic (n = 34, 41%), and acupuncture (n = 27, 33%) as most desired. Seventeen patients (21%) expressed interest in movement therapies.

Barriers to Integrative Therapies Use

When asked about barriers to use, 26 PCPs (93%) identified access to services as a somewhat or extremely likely barrier, and 22 identified time constraints (79%) (Table 3). However, 17 PCPs (61%) noted lack of familiarity, and 18 (64%) noted a lack of scientific evidence as barriers to recommending integrative modalities. Among patients, 33 (40%) indicated not knowing what services were available at their facility as a barrier, 32 (39%) were not familiar with specific therapies, and 21 (25%) indicated a lack of clarity about the benefits of a specific therapy. Only 14 patients (17%) indicated that there were no obstacles to use.

DISCUSSION

Use of integrative therapies, including complementary treatments, is an increasingly important part of chronic pain management. This survey study suggests VA PCPs are willing to recommend integrative therapies and patients with chronic back pain both desire and use several therapies. Moreover, both groups expressed interest in greater availability of similar therapies. The results also highlight key barriers, such as knowledge gaps, that should be addressed to increase the uptake of integrative modalities for managing chronic pain.

An increasing number of US adults are using complementary health approaches, an important component of integrative therapy.¹² This trend includes an increase in use for pain management, from 42.3% in 2002 to 49.2% in 2022; chiropractic care, acupuncture, and massage were most frequently used.¹² Similarly, chiropractic, acupuncture and massage were most often used by this sample of veterans with chronic back pain and were identified by the highest percentages of PCPs and patients as the therapies they would most like available.

There were areas where the opinions of patients and clinicians differed. As has been seen previously reported, clinicians largely recommended cognitive-behavioral therapy while patients showed less interest.¹⁷ Additionally, while patients expressed interest in the availability of movement therapies, such as yoga, PCPs expressed more interest in other strategies, such as trigger point injections. These differences may reflect true preference or a tendency for clinicians and patients to select therapies with which they are more familiar. Additional research is needed to better understand the acceptability and potential use of integrative health treatments across a broad array of therapeutic options.

Despite VHA policy requiring facilities to provide certain complementary and integrative health modalities, almost all PCPs identified access to services as a major obstacle.¹⁵ Based on evidence and a rigorous vetting process, services currently required on-site, via telehealth, or through community partners include acupuncture and battlefield acupuncture (battlefield auricular acupuncture), biofeedback, clinical hypnosis, guided imagery, medical massage therapy, medication, tai chi/qigong, and yoga. Optional approaches, which may be made available to veterans, include chiropractic and healing touch. Outside the VHA, some states have introduced or enacted legislation mandating insurance coverage of nonpharmacological pain treatments.¹⁸ However, these requirements and mandates do not help address challenges such as the availability of trained/qualified practitioners.^19,20 Ensuring access to complementary and integrative health treatments requires a more concerted effort to ensure that supply meets demand. It is also important to acknowledge the budgetary and physical space constraints that further limit access to services. Although expansion and integration of integrative medicine services remain a priority within the VA Whole Health program, implementation is contingent on available financial and infrastructure resources.

Time was also identified by PCPs as a barrier to recommending integrative therapies to patients. Developing and implementing time-efficient communication strategies for patient education such as concise talking points and informational handouts could help address this barrier. Furthermore, leveraging existing programs and engaging the entire health care team in patient education and referral could help increase integrative and complementary therapy uptake and use.

Although access and time were identified as major barriers, these findings also suggest that PCP and patient knowledge are another target area for enhancing the use of complementary and integrative therapies. Like prior research, most clinicians identified a lack of familiarity with certain services and a lack of scientific evidence as extremely or somewhat likely to affect their ability to offer integrative services to patients with chronic pain.²¹ Likewise, about 40% of patients identified being unfamiliar with a specific therapy as one of the major obstacles to receiving integrative therapies, with a similar number identifying PCPs as a source of information. The lack of familiarity may be due in part to the evolving nomenclature, with terms such as alternative, complementary, and integrative used to describe approaches outside what is often considered conventional medicine.¹⁰ On the other hand, there has also been considerable expansion in the number of therapies within this domain, along with an expanding evidence base. This suggests a need for targeted educational strategies for clinicians and patients, which can be rapidly deployed and continuously adapted as new therapies and evidence emerge.

Limitations

There are some inherent limitations with a survey-based approach, including sampling, non-response, and social desirability biases. In addition, this study only included PCPs and patients affiliated with a single VA medical center. Steps to mitigate these limitations included maintaining survey anonymity and reporting information about respondent characteristics to enhance transparency about the representativeness of the study findings.

CONCLUSIONS

Expanding the use of nonpharmacological pain treatments, including integrative modalities, is essential for safe and effective chronic pain management and reducing opioid use. Our findings show that VA PCPs and patients with chronic back pain are interested in and have some experience with certain integrative therapies. However, even within the context of a health care system that supports the use of integrative therapies for chronic pain as part of whole person care, increasing uptake will require addressing access and time-related constraints as well as ongoing clinician and patient education.