Rheumatology News

TOPLINE:

Genetic markers, specifically tumor necrosis factor alpha receptor 2 (TNFR2) gene polymorphisms, may predict response to TNF inhibitor therapy in patients with rheumatoid arthritis (RA). This approach could optimize treatment and improve patient outcomes.

METHODOLOGY:

• The study aimed to determine if TNFR2 gene polymorphisms could serve as biomarkers for treatment responsiveness to TNF inhibitors.
• It included 52 adult patients with RA (average age, 57.4 years; mean body mass index, 31.4; 65% women; 80% White) who had a mean disease duration of 8.9 years and started treatment with a single TNF inhibitor (infliximab, adalimumab, etanercept, golimumab, or certolizumab pegol).
• TNFR2-M (methionine) and TNFR2-R(arginine) gene polymorphisms were identified using genomic DNA isolated from patients’ blood samples to determine M/M, M/R, or R/R genotypes.
• The primary outcome was nonresponse to TNF inhibitors, defined as discontinuation of medication in < 3 months.
• The relationship between TNF inhibitor responsiveness and TNFR2 gene polymorphisms was analyzed using univariable logistic regression.

TAKEAWAY:

• Genomic DNA analysis revealed that 28 patients were homozygous for methionine, 22 were heterozygous, and two were homozygous for arginine.
• Of these, 96.4% of patients with the M/M genotype were responders to TNF inhibitors, whereas 75% of those with the M/R genotype and 50% with the R/R genotype were responders.
• Patients with the M/M genotype had approximately 10 times higher odds of responding to TNF inhibitors than those with the M/R and R/R genotypes (odds ratio, 10.12; P = .04).

IN PRACTICE:

“Identifying predictors for nonresponsiveness to TNF antagonists based on TNFR2 gene polymorphisms may become a valuable tool for personalized medicine, allowing for a more specific TNF [inhibitor] therapy in RA patients,” the authors wrote. “Given that TNF [inhibitor] therapy is used for many autoimmune conditions beyond RA, this genotyping could potentially serve as a useful framework for personalized treatment strategies in other autoimmune diseases to delay or reduce disease progression overall.”

SOURCE:

This study was led by Elaine Husni, MD, MPH, Lerner Research Institute, Cleveland Clinic in Ohio. It was published online on November 7, 2024, in Seminars in Arthritis and Rheumatism and presented as a poster at the American College of Rheumatology (ACR) 2024 Annual Meeting.

LIMITATIONS:

This study’s sample size was relatively small.

DISCLOSURES:

This study was supported by the Arthritis Foundation and in part by the National Institutes of Health. No relevant conflicts of interest were disclosed by the authors.

This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

TOPLINE:

Genetic markers, specifically tumor necrosis factor alpha receptor 2 (TNFR2) gene polymorphisms, may predict response to TNF inhibitor therapy in patients with rheumatoid arthritis (RA). This approach could optimize treatment and improve patient outcomes.

METHODOLOGY:

• The study aimed to determine if TNFR2 gene polymorphisms could serve as biomarkers for treatment responsiveness to TNF inhibitors.
• It included 52 adult patients with RA (average age, 57.4 years; mean body mass index, 31.4; 65% women; 80% White) who had a mean disease duration of 8.9 years and started treatment with a single TNF inhibitor (infliximab, adalimumab, etanercept, golimumab, or certolizumab pegol).
• TNFR2-M (methionine) and TNFR2-R(arginine) gene polymorphisms were identified using genomic DNA isolated from patients’ blood samples to determine M/M, M/R, or R/R genotypes.
• The primary outcome was nonresponse to TNF inhibitors, defined as discontinuation of medication in < 3 months.
• The relationship between TNF inhibitor responsiveness and TNFR2 gene polymorphisms was analyzed using univariable logistic regression.

TAKEAWAY:

• Genomic DNA analysis revealed that 28 patients were homozygous for methionine, 22 were heterozygous, and two were homozygous for arginine.
• Of these, 96.4% of patients with the M/M genotype were responders to TNF inhibitors, whereas 75% of those with the M/R genotype and 50% with the R/R genotype were responders.
• Patients with the M/M genotype had approximately 10 times higher odds of responding to TNF inhibitors than those with the M/R and R/R genotypes (odds ratio, 10.12; P = .04).

IN PRACTICE:

“Identifying predictors for nonresponsiveness to TNF antagonists based on TNFR2 gene polymorphisms may become a valuable tool for personalized medicine, allowing for a more specific TNF [inhibitor] therapy in RA patients,” the authors wrote. “Given that TNF [inhibitor] therapy is used for many autoimmune conditions beyond RA, this genotyping could potentially serve as a useful framework for personalized treatment strategies in other autoimmune diseases to delay or reduce disease progression overall.”

SOURCE:

This study was led by Elaine Husni, MD, MPH, Lerner Research Institute, Cleveland Clinic in Ohio. It was published online on November 7, 2024, in Seminars in Arthritis and Rheumatism and presented as a poster at the American College of Rheumatology (ACR) 2024 Annual Meeting.

LIMITATIONS:

This study’s sample size was relatively small.

DISCLOSURES:

This study was supported by the Arthritis Foundation and in part by the National Institutes of Health. No relevant conflicts of interest were disclosed by the authors.

This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

TOPLINE:

Genetic markers, specifically tumor necrosis factor alpha receptor 2 (TNFR2) gene polymorphisms, may predict response to TNF inhibitor therapy in patients with rheumatoid arthritis (RA). This approach could optimize treatment and improve patient outcomes.

METHODOLOGY:

• The study aimed to determine if TNFR2 gene polymorphisms could serve as biomarkers for treatment responsiveness to TNF inhibitors.
• It included 52 adult patients with RA (average age, 57.4 years; mean body mass index, 31.4; 65% women; 80% White) who had a mean disease duration of 8.9 years and started treatment with a single TNF inhibitor (infliximab, adalimumab, etanercept, golimumab, or certolizumab pegol).
• TNFR2-M (methionine) and TNFR2-R(arginine) gene polymorphisms were identified using genomic DNA isolated from patients’ blood samples to determine M/M, M/R, or R/R genotypes.
• The primary outcome was nonresponse to TNF inhibitors, defined as discontinuation of medication in < 3 months.
• The relationship between TNF inhibitor responsiveness and TNFR2 gene polymorphisms was analyzed using univariable logistic regression.

TAKEAWAY:

• Genomic DNA analysis revealed that 28 patients were homozygous for methionine, 22 were heterozygous, and two were homozygous for arginine.
• Of these, 96.4% of patients with the M/M genotype were responders to TNF inhibitors, whereas 75% of those with the M/R genotype and 50% with the R/R genotype were responders.
• Patients with the M/M genotype had approximately 10 times higher odds of responding to TNF inhibitors than those with the M/R and R/R genotypes (odds ratio, 10.12; P = .04).

IN PRACTICE:

“Identifying predictors for nonresponsiveness to TNF antagonists based on TNFR2 gene polymorphisms may become a valuable tool for personalized medicine, allowing for a more specific TNF [inhibitor] therapy in RA patients,” the authors wrote. “Given that TNF [inhibitor] therapy is used for many autoimmune conditions beyond RA, this genotyping could potentially serve as a useful framework for personalized treatment strategies in other autoimmune diseases to delay or reduce disease progression overall.”

SOURCE:

This study was led by Elaine Husni, MD, MPH, Lerner Research Institute, Cleveland Clinic in Ohio. It was published online on November 7, 2024, in Seminars in Arthritis and Rheumatism and presented as a poster at the American College of Rheumatology (ACR) 2024 Annual Meeting.

LIMITATIONS:

This study’s sample size was relatively small.

DISCLOSURES:

This study was supported by the Arthritis Foundation and in part by the National Institutes of Health. No relevant conflicts of interest were disclosed by the authors.

This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

Cultural competency is one of the most important values in the practice of medicine. Defined as the “ability to collaborate effectively with individuals from different cultures,” this type of competence “improves healthcare experiences and outcomes.” But within the context of cultural familiarity, it’s equally important to “understand that each person is an individual and may or may not adhere to certain cultural beliefs or practices common in his or her culture,” according to the Agency for Healthcare Research and Quality’s (AHRQ’s) Health Literacy Universal Precautions Toolkit.

Sarah Candler, MD, MPH, an internal medicine physician specializing in primary care for older adults in Washington, DC, said that the medical code of ethics consists of several pillars, with patient autonomy as the “first and most primary of those pillars.” She calls the balance of patient autonomy and cultural respect a “complicated tightrope to walk,” but says that these ethical principles can inform medical decisions and the patient-physician relationship.

 

Cultural Familiarity

It’s important to be as familiar as possible with the patient’s culture, Santina Wheat, MD, program director, Northwestern McGaw Family Medicine Residency at Delnor Hospital, Geneva, told this news organization. “For example, we serve many Orthodox Jewish patients. We had a meeting with rabbis from the community to present to us what religious laws might affect our patients. Until recently, I was delivering babies, and there was always a 24-hour emergency rabbi on call if an Orthodox patient wanted the input of a rabbi into her decisions.”

Jay W. Lee, MD, MPH, a member of the board of directors of the American Academy of Family Physicians, also sets out to educate himself about the cultural norms of his patients if they come from populations he’s not familiar with. “For example, this comes up when a new refugee population comes to the United States — most recently, there was a population of Afghan refugees,” Lee told this news organization.

Lee spent “a lot of time trying to learn about their cultural norms,” which prepared him to “ask more targeted questions about the patient’s understanding of the tests we were ordering or treatment options we were bringing forward.”

Lee, also the medical director at Integrated Health Partners of Southern California and associate clinical professor of family medicine at the University of California, Irvine, said it might be best if the physician is “language congruent or culturally similar.” Lee is of Asian descent and also speaks Spanish fluently. “I enjoy cultural exchanges with my patients, and I encourage patients to find a physician who’s the best fit.” But being from the same culture isn’t absolutely necessary for building relationships with the patient. “The key is offering the patient autonomy” while understanding the cultural context.

 

Don’t Assume ... Always Ask

Cultural familiarity doesn’t equate with stereotyping, Wheat emphasized. “Proceeding without assumptions opens the opportunity to ask questions for clarification and understanding and to improve patient care,” said Lee.

Sara Glass, PhD, LCSW, agrees. She’s the clinical director of Soul Wellness NYC, New York City, a psychotherapy practice that specializes in treating trauma. Based on her own experiences, she knows that some physicians and other healthcare professionals confuse cultural sensitivity with cultural stereotyping.

Glass, formerly Hasidic and ultra-Orthodox, shared an example from her own life. During the delivery of her second child, she sustained a vaginal tear. At her 6-week postpartum visit, her ob/gyn said, “Just remind me when you’re in your ninth month next time, and I can sew it up right after you deliver.”

Much of this physician’s practice “consisted of Hasidic women who looked just like me, wearing the same garb — head coverings such as wigs and scarves and long skirts. Most women in that community have multiple pregnancies,” Glass told this news organization. “My sister has 10 children, and that’s not unusual. The doctor simply assumed I’d be going on to have more babies without asking if that’s what I wanted.”

Glass says she was also never given information by her physician about the range of available contraceptive options. The rabbis of the Hasidic sect to which Glass belonged allowed women to practice contraception for 6 months following childbirth, or for longer, in the setting of certain medical conditions, but only certain types of birth control were religiously permissible. Other options were not mentioned to her by her physician, and she didn’t know that they existed.

Making no assumptions applies not only to patients from other cultures but also to all patients — including members of “mainstream American culture.”

Candler recalls a young patient with a new baby, who shared “how exhausted she was and how much time, energy, and work it took to care for children,” Candler recounted. “To me, it sounded as though she didn’t want another child, and I was about to offer contraception when it occurred to me to first ask if she wanted to have more children.” Candler was surprised when the patient said that, although she wasn’t actively looking to become pregnant again, she didn’t want to take preventive measures. “I’m so glad I asked, rather than simply assuming.”

 

Culture Is Mutable

Important questions to ask patients include whether there are aspects of their culture or religion that might affect their care — which can include medications they may feel uncomfortable using — and what family members they want to have involved in clinical discussions and decisions, said Wheat.

Lee described treating a refugee from Afghanistan who was in her sixth month of pregnancy. “I quickly needed to learn about what her expectations were for her care and my presence as a male on her care team,” he recounted. Lee arranged for the patient to receive prenatal care from a different clinician and arranged for follow-up for her husband and children. “Everyone had good results.”

Candler noted that some patients choose their physician specifically because that practitioner is conversant with their culture and respectful of its mores — especially when physicians share the same culture as the patient. But that level of familiarity can make it easy to forget to ask questions about the experience of the individual patient within that culture.

Moreover, Glass suggested, some physicians who treat patients from a particular culture or religious group may be concerned about offending them or antagonizing religious leaders if they discuss medical options that aren’t accepted or practiced in that community or culture, such as vasectomy for male contraception. “But that deprives patients of knowing what choices are available and making truly informed decisions.”

This is especially important because “culture is mutable,” said Candler, and religious or cultural practices can “look one way on paper but be implemented, adopted, or executed in a completely different way by every human being who lives in that culture.” The best cultural competency “comes from continuing to build relationships with our patients. But even in a single visit, a single hospitalization, we should get to know patients as human beings, not just members of a given culture.”

There are cultures in which families want to be the liaison between the patient and the physician and to make decisions on the patient’s behalf. “I always ask patients what role they want their family members to play even if the cultural expectation is that the family will be heavily involved,” Candler said.

Sometimes, this can be awkward, and families might become upset. Candler described an elderly, frail patient who was diagnosed with end-stage cancer. She had always relied heavily on family to care for her. Concerned about overburdening them, she didn’t want them to know her diagnosis. The patient was mentally competent to make that decision.

“Usually, I would have had the family at the bedside so I could be sure everyone was appropriately informed and prepared for what lay ahead, but in this case, I couldn’t do so,” Candler said. “I had to inform her entire care team not to discuss the cancer diagnosis with any family members because this was the patient’s express wish. And when the family asked me if the diagnosis was cancer, I had to respond, ‘I’m so sorry, but your loved one doesn’t want us to discuss details of her diagnosis.’”

Other patients don’t want to know their own diagnosis and specifically ask Candler to inform a family member. “I’ve had patients request that I tell their children. They want their children to make decisions on their behalf.”

The main thing, Candler emphasized, is to “ask the patient, make sure the patient is competent to make that decision, thoroughly document the patient’s decision in the chart, and respect whatever that decision is.”

 

You Can Revisit the Questions

Having a longitudinal relationship means that the physician can revisit the same questions at different junctures because people’s perspectives sometimes change over time. “Discussing what a patient wants isn’t necessarily a one-time occurrence,” Wheat said. For example, “I’ve had situations where a patient has been a member of Jehovah’s Witnesses and won’t accept blood products — like transfusions — in treatment. I tell these patients that if an emergent situation arises, I would like to have the conversation again.”

Of course, sometimes patients are seen in the emergency department or in other situations where the physician has no prior relationship with them. “I always go into a room, especially with new patients, aiming to build rapport, communicate with a high level of respect, introduce myself, explain my approach, and understand the patient’s wishes,” Lee said. “As scenarios play out, I ask in multiple ways for the patient to confirm those wishes.”

He acknowledges that this can be time-consuming, “but it helps ensure the care that patient receives is complete, thorough, comprehensive, and respectful of the patient’s values and wishes.”

Candler disclosed paid part-time clinical work at CuraCapitol Primary Care Services, volunteer advocacy (reimbursed for travel) for the American College of Physicians, volunteer advocacy (reimbursed for travel) for the American Medical Association while serving on their Task Force to Preserve the Patient-Physician Relationship, and serving as a partner representative (reimbursed for time) for the AHRQ’s Person-Centered Care Planning Partnership, representing the American College of Physicians. Lee, Wheat, and Glass disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Cultural competency is one of the most important values in the practice of medicine. Defined as the “ability to collaborate effectively with individuals from different cultures,” this type of competence “improves healthcare experiences and outcomes.” But within the context of cultural familiarity, it’s equally important to “understand that each person is an individual and may or may not adhere to certain cultural beliefs or practices common in his or her culture,” according to the Agency for Healthcare Research and Quality’s (AHRQ’s) Health Literacy Universal Precautions Toolkit.

Sarah Candler, MD, MPH, an internal medicine physician specializing in primary care for older adults in Washington, DC, said that the medical code of ethics consists of several pillars, with patient autonomy as the “first and most primary of those pillars.” She calls the balance of patient autonomy and cultural respect a “complicated tightrope to walk,” but says that these ethical principles can inform medical decisions and the patient-physician relationship.

 

Cultural Familiarity

It’s important to be as familiar as possible with the patient’s culture, Santina Wheat, MD, program director, Northwestern McGaw Family Medicine Residency at Delnor Hospital, Geneva, told this news organization. “For example, we serve many Orthodox Jewish patients. We had a meeting with rabbis from the community to present to us what religious laws might affect our patients. Until recently, I was delivering babies, and there was always a 24-hour emergency rabbi on call if an Orthodox patient wanted the input of a rabbi into her decisions.”

Jay W. Lee, MD, MPH, a member of the board of directors of the American Academy of Family Physicians, also sets out to educate himself about the cultural norms of his patients if they come from populations he’s not familiar with. “For example, this comes up when a new refugee population comes to the United States — most recently, there was a population of Afghan refugees,” Lee told this news organization.

Lee spent “a lot of time trying to learn about their cultural norms,” which prepared him to “ask more targeted questions about the patient’s understanding of the tests we were ordering or treatment options we were bringing forward.”

Lee, also the medical director at Integrated Health Partners of Southern California and associate clinical professor of family medicine at the University of California, Irvine, said it might be best if the physician is “language congruent or culturally similar.” Lee is of Asian descent and also speaks Spanish fluently. “I enjoy cultural exchanges with my patients, and I encourage patients to find a physician who’s the best fit.” But being from the same culture isn’t absolutely necessary for building relationships with the patient. “The key is offering the patient autonomy” while understanding the cultural context.

 

Don’t Assume ... Always Ask

Cultural familiarity doesn’t equate with stereotyping, Wheat emphasized. “Proceeding without assumptions opens the opportunity to ask questions for clarification and understanding and to improve patient care,” said Lee.

Sara Glass, PhD, LCSW, agrees. She’s the clinical director of Soul Wellness NYC, New York City, a psychotherapy practice that specializes in treating trauma. Based on her own experiences, she knows that some physicians and other healthcare professionals confuse cultural sensitivity with cultural stereotyping.

Glass, formerly Hasidic and ultra-Orthodox, shared an example from her own life. During the delivery of her second child, she sustained a vaginal tear. At her 6-week postpartum visit, her ob/gyn said, “Just remind me when you’re in your ninth month next time, and I can sew it up right after you deliver.”

Much of this physician’s practice “consisted of Hasidic women who looked just like me, wearing the same garb — head coverings such as wigs and scarves and long skirts. Most women in that community have multiple pregnancies,” Glass told this news organization. “My sister has 10 children, and that’s not unusual. The doctor simply assumed I’d be going on to have more babies without asking if that’s what I wanted.”

Glass says she was also never given information by her physician about the range of available contraceptive options. The rabbis of the Hasidic sect to which Glass belonged allowed women to practice contraception for 6 months following childbirth, or for longer, in the setting of certain medical conditions, but only certain types of birth control were religiously permissible. Other options were not mentioned to her by her physician, and she didn’t know that they existed.

Making no assumptions applies not only to patients from other cultures but also to all patients — including members of “mainstream American culture.”

Candler recalls a young patient with a new baby, who shared “how exhausted she was and how much time, energy, and work it took to care for children,” Candler recounted. “To me, it sounded as though she didn’t want another child, and I was about to offer contraception when it occurred to me to first ask if she wanted to have more children.” Candler was surprised when the patient said that, although she wasn’t actively looking to become pregnant again, she didn’t want to take preventive measures. “I’m so glad I asked, rather than simply assuming.”

 

Culture Is Mutable

Important questions to ask patients include whether there are aspects of their culture or religion that might affect their care — which can include medications they may feel uncomfortable using — and what family members they want to have involved in clinical discussions and decisions, said Wheat.

Lee described treating a refugee from Afghanistan who was in her sixth month of pregnancy. “I quickly needed to learn about what her expectations were for her care and my presence as a male on her care team,” he recounted. Lee arranged for the patient to receive prenatal care from a different clinician and arranged for follow-up for her husband and children. “Everyone had good results.”

Candler noted that some patients choose their physician specifically because that practitioner is conversant with their culture and respectful of its mores — especially when physicians share the same culture as the patient. But that level of familiarity can make it easy to forget to ask questions about the experience of the individual patient within that culture.

Moreover, Glass suggested, some physicians who treat patients from a particular culture or religious group may be concerned about offending them or antagonizing religious leaders if they discuss medical options that aren’t accepted or practiced in that community or culture, such as vasectomy for male contraception. “But that deprives patients of knowing what choices are available and making truly informed decisions.”

This is especially important because “culture is mutable,” said Candler, and religious or cultural practices can “look one way on paper but be implemented, adopted, or executed in a completely different way by every human being who lives in that culture.” The best cultural competency “comes from continuing to build relationships with our patients. But even in a single visit, a single hospitalization, we should get to know patients as human beings, not just members of a given culture.”

There are cultures in which families want to be the liaison between the patient and the physician and to make decisions on the patient’s behalf. “I always ask patients what role they want their family members to play even if the cultural expectation is that the family will be heavily involved,” Candler said.

Sometimes, this can be awkward, and families might become upset. Candler described an elderly, frail patient who was diagnosed with end-stage cancer. She had always relied heavily on family to care for her. Concerned about overburdening them, she didn’t want them to know her diagnosis. The patient was mentally competent to make that decision.

“Usually, I would have had the family at the bedside so I could be sure everyone was appropriately informed and prepared for what lay ahead, but in this case, I couldn’t do so,” Candler said. “I had to inform her entire care team not to discuss the cancer diagnosis with any family members because this was the patient’s express wish. And when the family asked me if the diagnosis was cancer, I had to respond, ‘I’m so sorry, but your loved one doesn’t want us to discuss details of her diagnosis.’”

Other patients don’t want to know their own diagnosis and specifically ask Candler to inform a family member. “I’ve had patients request that I tell their children. They want their children to make decisions on their behalf.”

The main thing, Candler emphasized, is to “ask the patient, make sure the patient is competent to make that decision, thoroughly document the patient’s decision in the chart, and respect whatever that decision is.”

 

You Can Revisit the Questions

Having a longitudinal relationship means that the physician can revisit the same questions at different junctures because people’s perspectives sometimes change over time. “Discussing what a patient wants isn’t necessarily a one-time occurrence,” Wheat said. For example, “I’ve had situations where a patient has been a member of Jehovah’s Witnesses and won’t accept blood products — like transfusions — in treatment. I tell these patients that if an emergent situation arises, I would like to have the conversation again.”

Of course, sometimes patients are seen in the emergency department or in other situations where the physician has no prior relationship with them. “I always go into a room, especially with new patients, aiming to build rapport, communicate with a high level of respect, introduce myself, explain my approach, and understand the patient’s wishes,” Lee said. “As scenarios play out, I ask in multiple ways for the patient to confirm those wishes.”

He acknowledges that this can be time-consuming, “but it helps ensure the care that patient receives is complete, thorough, comprehensive, and respectful of the patient’s values and wishes.”

Candler disclosed paid part-time clinical work at CuraCapitol Primary Care Services, volunteer advocacy (reimbursed for travel) for the American College of Physicians, volunteer advocacy (reimbursed for travel) for the American Medical Association while serving on their Task Force to Preserve the Patient-Physician Relationship, and serving as a partner representative (reimbursed for time) for the AHRQ’s Person-Centered Care Planning Partnership, representing the American College of Physicians. Lee, Wheat, and Glass disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Cultural competency is one of the most important values in the practice of medicine. Defined as the “ability to collaborate effectively with individuals from different cultures,” this type of competence “improves healthcare experiences and outcomes.” But within the context of cultural familiarity, it’s equally important to “understand that each person is an individual and may or may not adhere to certain cultural beliefs or practices common in his or her culture,” according to the Agency for Healthcare Research and Quality’s (AHRQ’s) Health Literacy Universal Precautions Toolkit.

Sarah Candler, MD, MPH, an internal medicine physician specializing in primary care for older adults in Washington, DC, said that the medical code of ethics consists of several pillars, with patient autonomy as the “first and most primary of those pillars.” She calls the balance of patient autonomy and cultural respect a “complicated tightrope to walk,” but says that these ethical principles can inform medical decisions and the patient-physician relationship.

 

Cultural Familiarity

It’s important to be as familiar as possible with the patient’s culture, Santina Wheat, MD, program director, Northwestern McGaw Family Medicine Residency at Delnor Hospital, Geneva, told this news organization. “For example, we serve many Orthodox Jewish patients. We had a meeting with rabbis from the community to present to us what religious laws might affect our patients. Until recently, I was delivering babies, and there was always a 24-hour emergency rabbi on call if an Orthodox patient wanted the input of a rabbi into her decisions.”

Jay W. Lee, MD, MPH, a member of the board of directors of the American Academy of Family Physicians, also sets out to educate himself about the cultural norms of his patients if they come from populations he’s not familiar with. “For example, this comes up when a new refugee population comes to the United States — most recently, there was a population of Afghan refugees,” Lee told this news organization.

Lee spent “a lot of time trying to learn about their cultural norms,” which prepared him to “ask more targeted questions about the patient’s understanding of the tests we were ordering or treatment options we were bringing forward.”

Lee, also the medical director at Integrated Health Partners of Southern California and associate clinical professor of family medicine at the University of California, Irvine, said it might be best if the physician is “language congruent or culturally similar.” Lee is of Asian descent and also speaks Spanish fluently. “I enjoy cultural exchanges with my patients, and I encourage patients to find a physician who’s the best fit.” But being from the same culture isn’t absolutely necessary for building relationships with the patient. “The key is offering the patient autonomy” while understanding the cultural context.

 

Don’t Assume ... Always Ask

Cultural familiarity doesn’t equate with stereotyping, Wheat emphasized. “Proceeding without assumptions opens the opportunity to ask questions for clarification and understanding and to improve patient care,” said Lee.

Sara Glass, PhD, LCSW, agrees. She’s the clinical director of Soul Wellness NYC, New York City, a psychotherapy practice that specializes in treating trauma. Based on her own experiences, she knows that some physicians and other healthcare professionals confuse cultural sensitivity with cultural stereotyping.

Glass, formerly Hasidic and ultra-Orthodox, shared an example from her own life. During the delivery of her second child, she sustained a vaginal tear. At her 6-week postpartum visit, her ob/gyn said, “Just remind me when you’re in your ninth month next time, and I can sew it up right after you deliver.”

Much of this physician’s practice “consisted of Hasidic women who looked just like me, wearing the same garb — head coverings such as wigs and scarves and long skirts. Most women in that community have multiple pregnancies,” Glass told this news organization. “My sister has 10 children, and that’s not unusual. The doctor simply assumed I’d be going on to have more babies without asking if that’s what I wanted.”

Glass says she was also never given information by her physician about the range of available contraceptive options. The rabbis of the Hasidic sect to which Glass belonged allowed women to practice contraception for 6 months following childbirth, or for longer, in the setting of certain medical conditions, but only certain types of birth control were religiously permissible. Other options were not mentioned to her by her physician, and she didn’t know that they existed.

Making no assumptions applies not only to patients from other cultures but also to all patients — including members of “mainstream American culture.”

Candler recalls a young patient with a new baby, who shared “how exhausted she was and how much time, energy, and work it took to care for children,” Candler recounted. “To me, it sounded as though she didn’t want another child, and I was about to offer contraception when it occurred to me to first ask if she wanted to have more children.” Candler was surprised when the patient said that, although she wasn’t actively looking to become pregnant again, she didn’t want to take preventive measures. “I’m so glad I asked, rather than simply assuming.”

 

Culture Is Mutable

Important questions to ask patients include whether there are aspects of their culture or religion that might affect their care — which can include medications they may feel uncomfortable using — and what family members they want to have involved in clinical discussions and decisions, said Wheat.

Lee described treating a refugee from Afghanistan who was in her sixth month of pregnancy. “I quickly needed to learn about what her expectations were for her care and my presence as a male on her care team,” he recounted. Lee arranged for the patient to receive prenatal care from a different clinician and arranged for follow-up for her husband and children. “Everyone had good results.”

Candler noted that some patients choose their physician specifically because that practitioner is conversant with their culture and respectful of its mores — especially when physicians share the same culture as the patient. But that level of familiarity can make it easy to forget to ask questions about the experience of the individual patient within that culture.

Moreover, Glass suggested, some physicians who treat patients from a particular culture or religious group may be concerned about offending them or antagonizing religious leaders if they discuss medical options that aren’t accepted or practiced in that community or culture, such as vasectomy for male contraception. “But that deprives patients of knowing what choices are available and making truly informed decisions.”

This is especially important because “culture is mutable,” said Candler, and religious or cultural practices can “look one way on paper but be implemented, adopted, or executed in a completely different way by every human being who lives in that culture.” The best cultural competency “comes from continuing to build relationships with our patients. But even in a single visit, a single hospitalization, we should get to know patients as human beings, not just members of a given culture.”

There are cultures in which families want to be the liaison between the patient and the physician and to make decisions on the patient’s behalf. “I always ask patients what role they want their family members to play even if the cultural expectation is that the family will be heavily involved,” Candler said.

Sometimes, this can be awkward, and families might become upset. Candler described an elderly, frail patient who was diagnosed with end-stage cancer. She had always relied heavily on family to care for her. Concerned about overburdening them, she didn’t want them to know her diagnosis. The patient was mentally competent to make that decision.

“Usually, I would have had the family at the bedside so I could be sure everyone was appropriately informed and prepared for what lay ahead, but in this case, I couldn’t do so,” Candler said. “I had to inform her entire care team not to discuss the cancer diagnosis with any family members because this was the patient’s express wish. And when the family asked me if the diagnosis was cancer, I had to respond, ‘I’m so sorry, but your loved one doesn’t want us to discuss details of her diagnosis.’”

Other patients don’t want to know their own diagnosis and specifically ask Candler to inform a family member. “I’ve had patients request that I tell their children. They want their children to make decisions on their behalf.”

The main thing, Candler emphasized, is to “ask the patient, make sure the patient is competent to make that decision, thoroughly document the patient’s decision in the chart, and respect whatever that decision is.”

 

You Can Revisit the Questions

Having a longitudinal relationship means that the physician can revisit the same questions at different junctures because people’s perspectives sometimes change over time. “Discussing what a patient wants isn’t necessarily a one-time occurrence,” Wheat said. For example, “I’ve had situations where a patient has been a member of Jehovah’s Witnesses and won’t accept blood products — like transfusions — in treatment. I tell these patients that if an emergent situation arises, I would like to have the conversation again.”

Of course, sometimes patients are seen in the emergency department or in other situations where the physician has no prior relationship with them. “I always go into a room, especially with new patients, aiming to build rapport, communicate with a high level of respect, introduce myself, explain my approach, and understand the patient’s wishes,” Lee said. “As scenarios play out, I ask in multiple ways for the patient to confirm those wishes.”

He acknowledges that this can be time-consuming, “but it helps ensure the care that patient receives is complete, thorough, comprehensive, and respectful of the patient’s values and wishes.”

Candler disclosed paid part-time clinical work at CuraCapitol Primary Care Services, volunteer advocacy (reimbursed for travel) for the American College of Physicians, volunteer advocacy (reimbursed for travel) for the American Medical Association while serving on their Task Force to Preserve the Patient-Physician Relationship, and serving as a partner representative (reimbursed for time) for the AHRQ’s Person-Centered Care Planning Partnership, representing the American College of Physicians. Lee, Wheat, and Glass disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children. 

Hatice, can you tell us about your career path?

I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.

Where did the issues arise?

Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”

So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.

It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.” 

In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”

 

Did you return to work part-time after your maternity leave, or full-time?

I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.

What happened next?

I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.

Did you apply elsewhere to improve your situation?

Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”

You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?

I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.

This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?

It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.

Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?

Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.

Returning to structural issues, how is your situation now — can you continue your training?

I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.

Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?

It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.

Is there anything else you’d like to share?

I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.

Thank you, Hatice, and best of luck in your career.

Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.

This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children. 

Hatice, can you tell us about your career path?

I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.

Where did the issues arise?

Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”

So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.

It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.” 

In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”

 

Did you return to work part-time after your maternity leave, or full-time?

I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.

What happened next?

I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.

Did you apply elsewhere to improve your situation?

Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”

You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?

I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.

This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?

It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.

Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?

Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.

Returning to structural issues, how is your situation now — can you continue your training?

I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.

Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?

It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.

Is there anything else you’d like to share?

I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.

Thank you, Hatice, and best of luck in your career.

Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.

This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children. 

Hatice, can you tell us about your career path?

I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.

Where did the issues arise?

Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”

So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.

It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.” 

In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”

 

Did you return to work part-time after your maternity leave, or full-time?

I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.

What happened next?

I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.

Did you apply elsewhere to improve your situation?

Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”

You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?

I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.

This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?

It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.

Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?

Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.

Returning to structural issues, how is your situation now — can you continue your training?

I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.

Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?

It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.

Is there anything else you’d like to share?

I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.

Thank you, Hatice, and best of luck in your career.

Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.

This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

A version of this article first appeared on Medscape.com.

The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?

Short answer: No. At least not yet.

The longer answer goes something like this:

A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.

“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”

This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.

Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.

“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.

“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.

Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.

It took him 3 years to model just four mutations.

AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.

 

New Windows into Protein Dynamics

By predicting protein structural details, AlphaFold models also made it possible to predict pockets where drugs could bind.

A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”

Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.

“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”

To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.

“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.

A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.

 

Complementary Tools to Speed Up Discovery 

Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.

Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.

Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.

“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.

PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.

“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.

This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.

The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.

PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.

“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.

Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.

“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”

 

And It Wouldn’t be an AI Mission Without ChatGPT

Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.

First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.

“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”

Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.

“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”

A version of this article first appeared on Medscape.com.

The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?

Short answer: No. At least not yet.

The longer answer goes something like this:

A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.

“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”

This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.

Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.

“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.

“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.

Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.

It took him 3 years to model just four mutations.

AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.

 

New Windows into Protein Dynamics

By predicting protein structural details, AlphaFold models also made it possible to predict pockets where drugs could bind.

A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”

Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.

“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”

To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.

“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.

A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.

 

Complementary Tools to Speed Up Discovery 

Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.

Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.

Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.

“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.

PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.

“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.

This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.

The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.

PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.

“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.

Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.

“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”

 

And It Wouldn’t be an AI Mission Without ChatGPT

Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.

First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.

“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”

Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.

“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”

A version of this article first appeared on Medscape.com.

The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?

Short answer: No. At least not yet.

The longer answer goes something like this:

A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.

“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”

This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.

Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.

“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.

“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.

Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.

It took him 3 years to model just four mutations.

AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.

 

New Windows into Protein Dynamics

By predicting protein structural details, AlphaFold models also made it possible to predict pockets where drugs could bind.

A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”

Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.

“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”

To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.

“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.

A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.

 

Complementary Tools to Speed Up Discovery 

Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.

Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.

Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.

“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.

PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.

“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.

This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.

The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.

PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.

“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.

Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.

“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”

 

And It Wouldn’t be an AI Mission Without ChatGPT

Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.

First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.

“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”

Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.

“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”

A version of this article first appeared on Medscape.com.

The Food and Drug Administration (FDA) has approved ustekinumab-stba (Steqeyma) as a biosimilar to the interleukin-12 and -23 inhibitor ustekinumab (Stelara) for the treatment of adults with active Crohn’s disease or ulcerative colitis and for both children aged ≥ 6 years and adults with moderate to severe plaque psoriasis or active psoriatic arthritis.

This is the seventh ustekinumab biosimilar approved by the FDA. The biosimilar, developed by Celltrion, has a license entry date in February 2025 as part of the settlement and license agreement with the manufacturer of the reference biologic, Johnson & Johnson.

Ustekinumab-stba will be available in two formulations: A subcutaneous injection in two strengths — a 45 mg/0.5 mL or 90 mg/1 mL solution in a single-dose, prefilled syringe — and an intravenous infusion of a 130 mg/26 mL (5 mg/mL) solution in a single-dose vial.

“The approval of Steqeyma reflects Celltrion’s continued investment in providing treatment options to patients diagnosed with ulcerative colitis, Crohn’s disease, psoriasis, and psoriatic arthritis,” said Thomas Nusbickel, Chief Commercial Officer at Celltrion USA, Jersey City, New Jersey, in a press release.

The FDA has previously approved the company’s adalimumab biosimilar Yuflyma and its infliximab biosimilar Zymfentra.

The full prescribing information for ustekinumab-stba is available here.

A version of this article first appeared on Medscape.com. 

The Food and Drug Administration (FDA) has approved ustekinumab-stba (Steqeyma) as a biosimilar to the interleukin-12 and -23 inhibitor ustekinumab (Stelara) for the treatment of adults with active Crohn’s disease or ulcerative colitis and for both children aged ≥ 6 years and adults with moderate to severe plaque psoriasis or active psoriatic arthritis.

This is the seventh ustekinumab biosimilar approved by the FDA. The biosimilar, developed by Celltrion, has a license entry date in February 2025 as part of the settlement and license agreement with the manufacturer of the reference biologic, Johnson & Johnson.

Ustekinumab-stba will be available in two formulations: A subcutaneous injection in two strengths — a 45 mg/0.5 mL or 90 mg/1 mL solution in a single-dose, prefilled syringe — and an intravenous infusion of a 130 mg/26 mL (5 mg/mL) solution in a single-dose vial.

“The approval of Steqeyma reflects Celltrion’s continued investment in providing treatment options to patients diagnosed with ulcerative colitis, Crohn’s disease, psoriasis, and psoriatic arthritis,” said Thomas Nusbickel, Chief Commercial Officer at Celltrion USA, Jersey City, New Jersey, in a press release.

The FDA has previously approved the company’s adalimumab biosimilar Yuflyma and its infliximab biosimilar Zymfentra.

The full prescribing information for ustekinumab-stba is available here.

A version of this article first appeared on Medscape.com. 

The Food and Drug Administration (FDA) has approved ustekinumab-stba (Steqeyma) as a biosimilar to the interleukin-12 and -23 inhibitor ustekinumab (Stelara) for the treatment of adults with active Crohn’s disease or ulcerative colitis and for both children aged ≥ 6 years and adults with moderate to severe plaque psoriasis or active psoriatic arthritis.

This is the seventh ustekinumab biosimilar approved by the FDA. The biosimilar, developed by Celltrion, has a license entry date in February 2025 as part of the settlement and license agreement with the manufacturer of the reference biologic, Johnson & Johnson.

Ustekinumab-stba will be available in two formulations: A subcutaneous injection in two strengths — a 45 mg/0.5 mL or 90 mg/1 mL solution in a single-dose, prefilled syringe — and an intravenous infusion of a 130 mg/26 mL (5 mg/mL) solution in a single-dose vial.

“The approval of Steqeyma reflects Celltrion’s continued investment in providing treatment options to patients diagnosed with ulcerative colitis, Crohn’s disease, psoriasis, and psoriatic arthritis,” said Thomas Nusbickel, Chief Commercial Officer at Celltrion USA, Jersey City, New Jersey, in a press release.

The FDA has previously approved the company’s adalimumab biosimilar Yuflyma and its infliximab biosimilar Zymfentra.

The full prescribing information for ustekinumab-stba is available here.

A version of this article first appeared on Medscape.com. 

This transcript has been edited for clarity. 

Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.

Rising Trend in Claim Denials and Financial Impact

First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem. 

Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.

 

Breakdown of Denial Rates and Costs

Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.

That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved. 

 

Common Reasons for Denials

Let’s take a look at major causes and what’s going on. 

Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied. 

The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial. 

Many times, these denials are done by an algorithm, not by individual people. 

What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options. 

When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid. 

 

Impact on Patient Care

Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either. 

The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.

We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.

 

How Can We Address This?

I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.

Also, if treatments or procedures are bundled, they can’t be filed separately. 

Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time. 

You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin. 

Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.

It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?

Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.

A version of this article first appeared on Medscape.com.

This transcript has been edited for clarity. 

Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.

Rising Trend in Claim Denials and Financial Impact

First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem. 

Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.

 

Breakdown of Denial Rates and Costs

Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.

That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved. 

 

Common Reasons for Denials

Let’s take a look at major causes and what’s going on. 

Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied. 

The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial. 

Many times, these denials are done by an algorithm, not by individual people. 

What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options. 

When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid. 

 

Impact on Patient Care

Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either. 

The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.

We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.

 

How Can We Address This?

I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.

Also, if treatments or procedures are bundled, they can’t be filed separately. 

Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time. 

You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin. 

Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.

It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?

Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.

A version of this article first appeared on Medscape.com.

This transcript has been edited for clarity. 

Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.

Rising Trend in Claim Denials and Financial Impact

First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem. 

Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.

 

Breakdown of Denial Rates and Costs

Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.

That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved. 

 

Common Reasons for Denials

Let’s take a look at major causes and what’s going on. 

Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied. 

The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial. 

Many times, these denials are done by an algorithm, not by individual people. 

What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options. 

When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid. 

 

Impact on Patient Care

Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either. 

The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.

We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.

 

How Can We Address This?

I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.

Also, if treatments or procedures are bundled, they can’t be filed separately. 

Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time. 

You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin. 

Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.

It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?

Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.

A version of this article first appeared on Medscape.com.

A new diagnostic test can accurately distinguish osteoarthritis (OA) from inflammatory arthritis using two synovial fluid biomarkers, according to research published in the Journal of Orthopaedic Research on December 18, 2024.

However, experts question whether such a test would be useful.

“The need would seem to be fairly limited, mostly those with single joint involvement and a lack of other systemic features to specify a diagnosis, which is not that common, at least in rheumatology, where there are usually features in the history and physical that can clarify the diagnosis,” said Amanda E. Nelson, MD, MSCR, professor of medicine in the Division of Rheumatology, Allergy, and Immunology at the University of North Carolina at Chapel Hill. She was not involved with the research.

The test uses an algorithm that incorporates concentrations of cartilage oligomeric matrix protein (COMP) and interleukin 8 (IL-8) in synovial fluid. The researchers hypothesized that a ratio of the two biomarkers could distinguish between primary OA and other inflammatory arthritic diagnoses.

“Primary OA is unlikely when either COMP concentration or COMP/IL‐8 ratio in the synovial fluid is low since these conditions indicate either lack of cartilage degradation or presence of high inflammation,” wrote Daniel Keter and coauthors at CD Diagnostics, Claymont, Delaware, and CD Laboratories, Towson, Maryland. “In contrast, a high COMP concentration result in combination with high COMP/IL‐8 ratio would be suggestive of low inflammation in the setting of cartilage deterioration, which is indicative of primary OA.”

In patients with OA, synovial fluid can be difficult to aspirate in sufficient amounts for testing, Nelson said.

“If synovial fluid is present and able to be aspirated, it is unclear if this test has any benefit over a simple, standard cell count and crystal assessment, which can also distinguish between osteoarthritis and more inflammatory arthritides,” she said.

 

Differentiating OA

To test this potential diagnostic algorithm, researchers obtained 171 knee synovial fluid samples from approved clinical remnant sample sources and a biovendor. All samples were annotated with an existing arthritic diagnosis, including 54 with primary OA, 57 with rheumatoid arthritis (RA), 30 with crystal arthritis (CA), and 30 with native septic arthritis (NSA).

Researchers assigned a CA diagnosis based on the presence of monosodium urate or calcium pyrophosphate dehydrate crystals in the synovial fluid, and NSA was determined via the Synovasure Alpha Defensin test. OA was confirmed via radiograph as Kellgren‐Lawrence grades 2‐4 with no other arthritic diagnoses. RA samples were purchased via a biovendor, and researchers were not provided with diagnosis‐confirming data.

All samples were randomized and blinded before testing, and researchers used enzyme-linked immunosorbent assay tests for both COMP and IL-8 biomarkers.

Of the 54 OA samples, 47 tested positive for OA using the COMP + COMP/IL-8 ratio algorithm. Of the 117 samples with inflammatory arthritis, 13 tested positive for OA. Overall, the diagnostic algorithm demonstrated a clinical sensitivity of 87.0% and specificity of 88.9%. The positive predictive value was 78.3%, while the negative predictive value was 93.7%.

 

Unclear Clinical Need

Nelson noted that while this test aims to differentiate between arthritic diagnoses, patients can also have multiple conditions.

“Many individuals with rheumatoid arthritis will develop osteoarthritis, but they can have both, so a yes/no test is of unclear utility,” she said. OA and calcium pyrophosphate deposition (CPPD) disease can often occur together, “but the driver is really the OA, and the CPPD is present but not actively inflammatory,” she continued. “Septic arthritis should be readily distinguishable by cell count alone [and again, can coexist with any of the other conditions], and a thorough history and physical should be able to differentiate in most cases.”

While these results from this study are “reasonably impressive,” more clinical information is needed to interpret these results, added C. Kent Kwoh, MD, director of the University of Arizona Arthritis Center and professor of medicine and medical imaging at the University of Arizona College of Medicine, Tucson, Arizona.

Because the study is retrospective in nature and researchers obtained specimens from different sources, it was not clear if these patients were being treated when these samples were taken and if their various conditions were controlled or flaring.

“I would say this is a reasonable first step,” Kwoh said. “We would need prospective studies, more clinical characterization, and potentially longitudinal studies to understand when this test may be useful.”

This research was internally funded by Zimmer Biomet. All authors were employees of CD Diagnostics or CD Laboratories, both of which are subsidiaries of Zimmer Biomet. Kwoh reported receiving grants or contracts with AbbVie, Artiva, Eli Lilly and Company, Bristol Myers Squibb, Cumberland, Pfizer, GSK, and Galapagos, and consulting fees from TrialSpark/Formation Bio, Express Scripts, GSK, TLC BioSciences, and AposHealth. He participates on Data Safety Monitoring or Advisory Boards of Moebius Medical, Sun Pharma, Novartis, Xalud, and Kolon TissueGene. Nelson reported no relevant disclosures.

 

A version of this article appeared on Medscape.com.

A new diagnostic test can accurately distinguish osteoarthritis (OA) from inflammatory arthritis using two synovial fluid biomarkers, according to research published in the Journal of Orthopaedic Research on December 18, 2024.

However, experts question whether such a test would be useful.

“The need would seem to be fairly limited, mostly those with single joint involvement and a lack of other systemic features to specify a diagnosis, which is not that common, at least in rheumatology, where there are usually features in the history and physical that can clarify the diagnosis,” said Amanda E. Nelson, MD, MSCR, professor of medicine in the Division of Rheumatology, Allergy, and Immunology at the University of North Carolina at Chapel Hill. She was not involved with the research.

The test uses an algorithm that incorporates concentrations of cartilage oligomeric matrix protein (COMP) and interleukin 8 (IL-8) in synovial fluid. The researchers hypothesized that a ratio of the two biomarkers could distinguish between primary OA and other inflammatory arthritic diagnoses.

“Primary OA is unlikely when either COMP concentration or COMP/IL‐8 ratio in the synovial fluid is low since these conditions indicate either lack of cartilage degradation or presence of high inflammation,” wrote Daniel Keter and coauthors at CD Diagnostics, Claymont, Delaware, and CD Laboratories, Towson, Maryland. “In contrast, a high COMP concentration result in combination with high COMP/IL‐8 ratio would be suggestive of low inflammation in the setting of cartilage deterioration, which is indicative of primary OA.”

In patients with OA, synovial fluid can be difficult to aspirate in sufficient amounts for testing, Nelson said.

“If synovial fluid is present and able to be aspirated, it is unclear if this test has any benefit over a simple, standard cell count and crystal assessment, which can also distinguish between osteoarthritis and more inflammatory arthritides,” she said.

 

Differentiating OA

To test this potential diagnostic algorithm, researchers obtained 171 knee synovial fluid samples from approved clinical remnant sample sources and a biovendor. All samples were annotated with an existing arthritic diagnosis, including 54 with primary OA, 57 with rheumatoid arthritis (RA), 30 with crystal arthritis (CA), and 30 with native septic arthritis (NSA).

Researchers assigned a CA diagnosis based on the presence of monosodium urate or calcium pyrophosphate dehydrate crystals in the synovial fluid, and NSA was determined via the Synovasure Alpha Defensin test. OA was confirmed via radiograph as Kellgren‐Lawrence grades 2‐4 with no other arthritic diagnoses. RA samples were purchased via a biovendor, and researchers were not provided with diagnosis‐confirming data.

All samples were randomized and blinded before testing, and researchers used enzyme-linked immunosorbent assay tests for both COMP and IL-8 biomarkers.

Of the 54 OA samples, 47 tested positive for OA using the COMP + COMP/IL-8 ratio algorithm. Of the 117 samples with inflammatory arthritis, 13 tested positive for OA. Overall, the diagnostic algorithm demonstrated a clinical sensitivity of 87.0% and specificity of 88.9%. The positive predictive value was 78.3%, while the negative predictive value was 93.7%.

 

Unclear Clinical Need

Nelson noted that while this test aims to differentiate between arthritic diagnoses, patients can also have multiple conditions.

“Many individuals with rheumatoid arthritis will develop osteoarthritis, but they can have both, so a yes/no test is of unclear utility,” she said. OA and calcium pyrophosphate deposition (CPPD) disease can often occur together, “but the driver is really the OA, and the CPPD is present but not actively inflammatory,” she continued. “Septic arthritis should be readily distinguishable by cell count alone [and again, can coexist with any of the other conditions], and a thorough history and physical should be able to differentiate in most cases.”

While these results from this study are “reasonably impressive,” more clinical information is needed to interpret these results, added C. Kent Kwoh, MD, director of the University of Arizona Arthritis Center and professor of medicine and medical imaging at the University of Arizona College of Medicine, Tucson, Arizona.

Because the study is retrospective in nature and researchers obtained specimens from different sources, it was not clear if these patients were being treated when these samples were taken and if their various conditions were controlled or flaring.

“I would say this is a reasonable first step,” Kwoh said. “We would need prospective studies, more clinical characterization, and potentially longitudinal studies to understand when this test may be useful.”

This research was internally funded by Zimmer Biomet. All authors were employees of CD Diagnostics or CD Laboratories, both of which are subsidiaries of Zimmer Biomet. Kwoh reported receiving grants or contracts with AbbVie, Artiva, Eli Lilly and Company, Bristol Myers Squibb, Cumberland, Pfizer, GSK, and Galapagos, and consulting fees from TrialSpark/Formation Bio, Express Scripts, GSK, TLC BioSciences, and AposHealth. He participates on Data Safety Monitoring or Advisory Boards of Moebius Medical, Sun Pharma, Novartis, Xalud, and Kolon TissueGene. Nelson reported no relevant disclosures.

 

A version of this article appeared on Medscape.com.

A new diagnostic test can accurately distinguish osteoarthritis (OA) from inflammatory arthritis using two synovial fluid biomarkers, according to research published in the Journal of Orthopaedic Research on December 18, 2024.

However, experts question whether such a test would be useful.

“The need would seem to be fairly limited, mostly those with single joint involvement and a lack of other systemic features to specify a diagnosis, which is not that common, at least in rheumatology, where there are usually features in the history and physical that can clarify the diagnosis,” said Amanda E. Nelson, MD, MSCR, professor of medicine in the Division of Rheumatology, Allergy, and Immunology at the University of North Carolina at Chapel Hill. She was not involved with the research.

The test uses an algorithm that incorporates concentrations of cartilage oligomeric matrix protein (COMP) and interleukin 8 (IL-8) in synovial fluid. The researchers hypothesized that a ratio of the two biomarkers could distinguish between primary OA and other inflammatory arthritic diagnoses.

“Primary OA is unlikely when either COMP concentration or COMP/IL‐8 ratio in the synovial fluid is low since these conditions indicate either lack of cartilage degradation or presence of high inflammation,” wrote Daniel Keter and coauthors at CD Diagnostics, Claymont, Delaware, and CD Laboratories, Towson, Maryland. “In contrast, a high COMP concentration result in combination with high COMP/IL‐8 ratio would be suggestive of low inflammation in the setting of cartilage deterioration, which is indicative of primary OA.”

In patients with OA, synovial fluid can be difficult to aspirate in sufficient amounts for testing, Nelson said.

“If synovial fluid is present and able to be aspirated, it is unclear if this test has any benefit over a simple, standard cell count and crystal assessment, which can also distinguish between osteoarthritis and more inflammatory arthritides,” she said.

 

Differentiating OA

To test this potential diagnostic algorithm, researchers obtained 171 knee synovial fluid samples from approved clinical remnant sample sources and a biovendor. All samples were annotated with an existing arthritic diagnosis, including 54 with primary OA, 57 with rheumatoid arthritis (RA), 30 with crystal arthritis (CA), and 30 with native septic arthritis (NSA).

Researchers assigned a CA diagnosis based on the presence of monosodium urate or calcium pyrophosphate dehydrate crystals in the synovial fluid, and NSA was determined via the Synovasure Alpha Defensin test. OA was confirmed via radiograph as Kellgren‐Lawrence grades 2‐4 with no other arthritic diagnoses. RA samples were purchased via a biovendor, and researchers were not provided with diagnosis‐confirming data.

All samples were randomized and blinded before testing, and researchers used enzyme-linked immunosorbent assay tests for both COMP and IL-8 biomarkers.

Of the 54 OA samples, 47 tested positive for OA using the COMP + COMP/IL-8 ratio algorithm. Of the 117 samples with inflammatory arthritis, 13 tested positive for OA. Overall, the diagnostic algorithm demonstrated a clinical sensitivity of 87.0% and specificity of 88.9%. The positive predictive value was 78.3%, while the negative predictive value was 93.7%.

 

Unclear Clinical Need

Nelson noted that while this test aims to differentiate between arthritic diagnoses, patients can also have multiple conditions.

“Many individuals with rheumatoid arthritis will develop osteoarthritis, but they can have both, so a yes/no test is of unclear utility,” she said. OA and calcium pyrophosphate deposition (CPPD) disease can often occur together, “but the driver is really the OA, and the CPPD is present but not actively inflammatory,” she continued. “Septic arthritis should be readily distinguishable by cell count alone [and again, can coexist with any of the other conditions], and a thorough history and physical should be able to differentiate in most cases.”

While these results from this study are “reasonably impressive,” more clinical information is needed to interpret these results, added C. Kent Kwoh, MD, director of the University of Arizona Arthritis Center and professor of medicine and medical imaging at the University of Arizona College of Medicine, Tucson, Arizona.

Because the study is retrospective in nature and researchers obtained specimens from different sources, it was not clear if these patients were being treated when these samples were taken and if their various conditions were controlled or flaring.

“I would say this is a reasonable first step,” Kwoh said. “We would need prospective studies, more clinical characterization, and potentially longitudinal studies to understand when this test may be useful.”

This research was internally funded by Zimmer Biomet. All authors were employees of CD Diagnostics or CD Laboratories, both of which are subsidiaries of Zimmer Biomet. Kwoh reported receiving grants or contracts with AbbVie, Artiva, Eli Lilly and Company, Bristol Myers Squibb, Cumberland, Pfizer, GSK, and Galapagos, and consulting fees from TrialSpark/Formation Bio, Express Scripts, GSK, TLC BioSciences, and AposHealth. He participates on Data Safety Monitoring or Advisory Boards of Moebius Medical, Sun Pharma, Novartis, Xalud, and Kolon TissueGene. Nelson reported no relevant disclosures.

 

A version of this article appeared on Medscape.com.

In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.

Increased Global Plastic Production

Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.

The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.

 

Minimal Plastic Waste Recycling

Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.

In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.

 

Methodological Challenges

However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.

“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.

A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.

A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.

 

Changes to the Microbiome

Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.

Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.

A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.

 

Health Affects High

The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.

The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.

BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.

Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.

The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.

Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.

Increased Global Plastic Production

Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.

The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.

 

Minimal Plastic Waste Recycling

Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.

In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.

 

Methodological Challenges

However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.

“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.

A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.

A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.

 

Changes to the Microbiome

Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.

Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.

A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.

 

Health Affects High

The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.

The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.

BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.

Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.

The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.

Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.

Increased Global Plastic Production

Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.

The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.

 

Minimal Plastic Waste Recycling

Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.

In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.

 

Methodological Challenges

However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.

“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.

A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.

A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.

 

Changes to the Microbiome

Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.

Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.

A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.

 

Health Affects High

The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.

The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.

BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.

Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.

The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.

Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.

This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.

TOPLINE:

CD19-targeting chimeric antigen receptor (CAR) T-cell therapy shows potential to intercept fibrotic organ manifestations and improve disease measures in patients with diffuse cutaneous systemic sclerosis (SSc) who had disease progression despite multiple previous treatments.

METHODOLOGY:

• Researchers conducted a case series to examine the effect of CD19-targeting CAR T-cell therapy on fibrotic and vascular organ manifestations in six patients with diffuse cutaneous SSc (median age, 42 years; four men and two women) who had an insufficient response to at least two previous treatments.
• Participants received CD19-targeting CAR T-cell treatment at a dose of 1 × 106 CAR T cells per kilogram of body weight after lymphodepletion with fludarabine and cyclophosphamide.
• The primary outcome was event-free time or treatment intensification after study entry, with events defined as the progression of interstitial lung disease, onset of congestive heart or renal failure or arterial hypertension, or initiation of new therapy.
• The secondary outcomes included changes in the modified Rodnan skin score (mRSS), imaging and laboratory assessments, patient-reported outcomes, and the modified American College of Rheumatology Composite Response Index in Systemic Sclerosis (ACR-CRISS), assessed at baseline and 3, 6, 9, and 12 months after treatment.

TAKEAWAY:

• No progression of organ manifestations or new lung, cardiac, or renal events occurred within the median follow-up period of 487 days.
• The probability of improvement in the ACR-CRISS score increased to a median value of 100% within 6 and 12 months of CAR T-cell treatment compared with baseline.
• Skin involvement improved in all the patients after CAR T-cell treatment, with a median mRSS decrease of 8 points within 100 days; the improvements were maintained throughout the 1-year follow-up period.
• This treatment also led to a depletion of antinuclear antibodies and SSc-specific autoantibodies.

IN PRACTICE:

“This case series highlights the potential of CAR T-cell therapy to address a crucial unmet need in refractory systemic sclerosis treatment. The study’s most significant contribution is the demonstration that CD19-targeting CAR T-cell therapy can halt or reverse aspects of fibrosis in systemic sclerosis,” Jérôme Avouac, Service de Rhumatologie, Hôpital Cochin, AP-HP Centre-Université Paris Cité, Paris, France, wrote in an accompanying editorial.

SOURCE:

The study was led by Janina Auth, MD, Deutsches Zentrum Immuntherapie, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen in Germany, and was published online on November 11, 2024, in The Lancet Rheumatology.

LIMITATIONS:

The study lacked a control group, which limited the ability to draw definitive conclusions about the efficacy of CD19-targeting CAR T-cell therapy compared with standard treatments. The unpredictable nature of SSc, in which periods of stability can occur spontaneously, makes it difficult to attribute the improvements merely to the intervention. Moreover, the effect of CAR T-cell therapy on other disease manifestations, such as pulmonary hypertension, myocardial involvement, and scleroderma renal crisis, remains unclear.

DISCLOSURES:

The study was funded by Deutsche Forschungsgemeinschaft, Deutsche Krebshilfe, ELAN Foundation Erlangen, Interdisziplinäres Zentrum für Klinische Forschung Erlangen, Bundesministerium für Bildung und Forschung, and the European Union. Some authors reported receiving research grants, consulting fees, speaker fees, honoraria, or travel grants from Boehringer Ingelheim, Novartis, Almirall, and other pharmaceutical companies.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

CD19-targeting chimeric antigen receptor (CAR) T-cell therapy shows potential to intercept fibrotic organ manifestations and improve disease measures in patients with diffuse cutaneous systemic sclerosis (SSc) who had disease progression despite multiple previous treatments.

METHODOLOGY:

• Researchers conducted a case series to examine the effect of CD19-targeting CAR T-cell therapy on fibrotic and vascular organ manifestations in six patients with diffuse cutaneous SSc (median age, 42 years; four men and two women) who had an insufficient response to at least two previous treatments.
• Participants received CD19-targeting CAR T-cell treatment at a dose of 1 × 106 CAR T cells per kilogram of body weight after lymphodepletion with fludarabine and cyclophosphamide.
• The primary outcome was event-free time or treatment intensification after study entry, with events defined as the progression of interstitial lung disease, onset of congestive heart or renal failure or arterial hypertension, or initiation of new therapy.
• The secondary outcomes included changes in the modified Rodnan skin score (mRSS), imaging and laboratory assessments, patient-reported outcomes, and the modified American College of Rheumatology Composite Response Index in Systemic Sclerosis (ACR-CRISS), assessed at baseline and 3, 6, 9, and 12 months after treatment.

TAKEAWAY:

• No progression of organ manifestations or new lung, cardiac, or renal events occurred within the median follow-up period of 487 days.
• The probability of improvement in the ACR-CRISS score increased to a median value of 100% within 6 and 12 months of CAR T-cell treatment compared with baseline.
• Skin involvement improved in all the patients after CAR T-cell treatment, with a median mRSS decrease of 8 points within 100 days; the improvements were maintained throughout the 1-year follow-up period.
• This treatment also led to a depletion of antinuclear antibodies and SSc-specific autoantibodies.

IN PRACTICE:

“This case series highlights the potential of CAR T-cell therapy to address a crucial unmet need in refractory systemic sclerosis treatment. The study’s most significant contribution is the demonstration that CD19-targeting CAR T-cell therapy can halt or reverse aspects of fibrosis in systemic sclerosis,” Jérôme Avouac, Service de Rhumatologie, Hôpital Cochin, AP-HP Centre-Université Paris Cité, Paris, France, wrote in an accompanying editorial.

SOURCE:

The study was led by Janina Auth, MD, Deutsches Zentrum Immuntherapie, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen in Germany, and was published online on November 11, 2024, in The Lancet Rheumatology.

LIMITATIONS:

The study lacked a control group, which limited the ability to draw definitive conclusions about the efficacy of CD19-targeting CAR T-cell therapy compared with standard treatments. The unpredictable nature of SSc, in which periods of stability can occur spontaneously, makes it difficult to attribute the improvements merely to the intervention. Moreover, the effect of CAR T-cell therapy on other disease manifestations, such as pulmonary hypertension, myocardial involvement, and scleroderma renal crisis, remains unclear.

DISCLOSURES:

The study was funded by Deutsche Forschungsgemeinschaft, Deutsche Krebshilfe, ELAN Foundation Erlangen, Interdisziplinäres Zentrum für Klinische Forschung Erlangen, Bundesministerium für Bildung und Forschung, and the European Union. Some authors reported receiving research grants, consulting fees, speaker fees, honoraria, or travel grants from Boehringer Ingelheim, Novartis, Almirall, and other pharmaceutical companies.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

CD19-targeting chimeric antigen receptor (CAR) T-cell therapy shows potential to intercept fibrotic organ manifestations and improve disease measures in patients with diffuse cutaneous systemic sclerosis (SSc) who had disease progression despite multiple previous treatments.

METHODOLOGY:

• Researchers conducted a case series to examine the effect of CD19-targeting CAR T-cell therapy on fibrotic and vascular organ manifestations in six patients with diffuse cutaneous SSc (median age, 42 years; four men and two women) who had an insufficient response to at least two previous treatments.
• Participants received CD19-targeting CAR T-cell treatment at a dose of 1 × 106 CAR T cells per kilogram of body weight after lymphodepletion with fludarabine and cyclophosphamide.
• The primary outcome was event-free time or treatment intensification after study entry, with events defined as the progression of interstitial lung disease, onset of congestive heart or renal failure or arterial hypertension, or initiation of new therapy.
• The secondary outcomes included changes in the modified Rodnan skin score (mRSS), imaging and laboratory assessments, patient-reported outcomes, and the modified American College of Rheumatology Composite Response Index in Systemic Sclerosis (ACR-CRISS), assessed at baseline and 3, 6, 9, and 12 months after treatment.

TAKEAWAY:

• No progression of organ manifestations or new lung, cardiac, or renal events occurred within the median follow-up period of 487 days.
• The probability of improvement in the ACR-CRISS score increased to a median value of 100% within 6 and 12 months of CAR T-cell treatment compared with baseline.
• Skin involvement improved in all the patients after CAR T-cell treatment, with a median mRSS decrease of 8 points within 100 days; the improvements were maintained throughout the 1-year follow-up period.
• This treatment also led to a depletion of antinuclear antibodies and SSc-specific autoantibodies.

IN PRACTICE:

“This case series highlights the potential of CAR T-cell therapy to address a crucial unmet need in refractory systemic sclerosis treatment. The study’s most significant contribution is the demonstration that CD19-targeting CAR T-cell therapy can halt or reverse aspects of fibrosis in systemic sclerosis,” Jérôme Avouac, Service de Rhumatologie, Hôpital Cochin, AP-HP Centre-Université Paris Cité, Paris, France, wrote in an accompanying editorial.

SOURCE:

The study was led by Janina Auth, MD, Deutsches Zentrum Immuntherapie, Friedrich-Alexander-Universität Erlangen-Nürnberg and Universitätsklinikum Erlangen in Germany, and was published online on November 11, 2024, in The Lancet Rheumatology.

LIMITATIONS:

The study lacked a control group, which limited the ability to draw definitive conclusions about the efficacy of CD19-targeting CAR T-cell therapy compared with standard treatments. The unpredictable nature of SSc, in which periods of stability can occur spontaneously, makes it difficult to attribute the improvements merely to the intervention. Moreover, the effect of CAR T-cell therapy on other disease manifestations, such as pulmonary hypertension, myocardial involvement, and scleroderma renal crisis, remains unclear.

DISCLOSURES:

The study was funded by Deutsche Forschungsgemeinschaft, Deutsche Krebshilfe, ELAN Foundation Erlangen, Interdisziplinäres Zentrum für Klinische Forschung Erlangen, Bundesministerium für Bildung und Forschung, and the European Union. Some authors reported receiving research grants, consulting fees, speaker fees, honoraria, or travel grants from Boehringer Ingelheim, Novartis, Almirall, and other pharmaceutical companies.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.

TOPLINE:

The initiation of biologic or targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs), particularly rituximab and abatacept, is associated with an increased risk for incident cancer in patients with rheumatoid arthritis (RA) within 2 years of starting treatment.

METHODOLOGY:

• The researchers conducted a retrospective cohort study to assess the safety of tumor necrosis factor (TNF) inhibitors, non-TNF inhibitors, and Janus kinase (JAK) inhibitors in patients with RA using US administrative claims data from the Merative Marketscan Research Databases from November 2012 to December 2021.
• A total of 25,305 patients with RA (median age, 50 years; 79% women; 49% from the southern United States) were identified using diagnostic codes on or before treatment initiation.
• Treatment exposures, including the initiation of TNF inhibitors (adalimumab, etanercept, certolizumab pegol, golimumab, and infliximab), non-TNF inhibitors (abatacept, interleukin 6 [IL-6] inhibitors, and rituximab), and JAK inhibitors (tofacitinib, baricitinib, and upadacitinib), were compared.
• The primary outcome was any incident cancer (excluding nonmelanoma skin cancer) occurring after a minimum of 90 days and within 2 years of treatment initiation.
• Sensitivity analyses used 1:1 propensity matching to compare cancer rates between populations treated with rituximab, IL-6 inhibitors, abatacept, or JAK inhibitors and matched reference populations treated with TNF inhibitors.

TAKEAWAY:

• Rituximab (adjusted hazard ratio [aHR], 1.91; 95% CI, 1.17-3.14) and abatacept (aHR, 1.47; 95% CI, 1.03-2.11) were significantly associated with an increased risk for incident cancer, compared with TNF inhibitors.
• In the propensity-matched analysis, a statistically significant increase in risk was observed in patients treated with rituximab (aHR, 4.37; 95% CI, 1.48-12.93) and abatacept (aHR, 3.12; 95%CI, 1.52-6.44).
• IL-6 inhibitors showed no significant association with cancer in the primary analysis, but a significantly increased risk was observed in the propensity-matched analysis (HR, 5.65; 95% CI, 1.11-28.79).
• JAK inhibitors were not associated with a significant increase in the risk for cancer, compared with TNF inhibitors.

IN PRACTICE:

“Given the limitations of using private insurance claims data and confounding by indication, it is likely that these patients may have a higher disease burden, resulting in channeling bias,” the authors wrote. “To understand these associations, larger studies with longer follow-up and more granular collection of data, including medication indications and RA disease activity measures, would be needed for better comparison of incident cancer risk among these drugs,” they added.