Tori Anglin

Purpose

Prostate cancer is the fifth leading cause of death in the United States. Genomic testing is essential to guide treatment decisions in patients with metastatic castration resistant prostate cancer (mCRPC), the most advanced stage of prostate cancer. However, identifying mCRPC patients from administrative data is challenging and hinders researchers’ ability to assess testing among these patients. This study aims to develop algorithms using structured data and unstructured data with Natural language processing (NLP) methods to identify veterans by disease stage and hormone sensitivity, and to assess patient characteristics as well as receipt of tumor NGS testing.

Methods

We used biopsy, pathology, and diagnosis codes, to identify veterans with newly diagnosed PC within the Veterans Health Administration (VA) from January 1, 2017 to December 31, 2020. We developed and deployed: 1. A structured algorithm that used medication and Prostate-Specific Antigen (PSA) data to assess hormone sensitivity. 2. NLP tools to extract disease stage and hormone sensitivity from clinical notes. We report descriptive statistics on patient demographics, clinical characteristics, disease status, androgen deprivation therapy (ADT), and receipt of tumor NGS testing.

Results

There were 42,485 veterans with newly diagnosed prostate cancer between 2017-2020. This represented ~0.18% of veterans served in the VA and consisted of Whites (57%), Blacks (33%), and others (10%). During the study period, 3,113 (7.3%) patients had documentation of assessment for intraductal carcinoma, 5,160 (12.1%) had ADT treatment, 1,481 (3.5%) had CRPC, and 3,246 (7.6%) had metastatic disease. Among the 42,485 veterans, 422 received tumor NGS testing within VA, and 300 of them had metastatic disease. NLP tool and structured data algorithm collectively showed that 38% of the 422 tumor NGS testing recipients had mCRPC. Among all newly diagnosed PC patients, White patients had highest rates of tumor-based testing (2.3%), then Native Hawaiians (1.7%), Asians and Blacks (1.2% each), compared to Native Americans (0.4%).

Implications

NLP tools alongside structured data algorithms successfully identified variables required to measure access to tumor NGS testing. Efforts to validate and apply this method is ongoing to assess receipt of precision prostate cancer care in VA.

Purpose

Prostate cancer is the fifth leading cause of death in the United States. Genomic testing is essential to guide treatment decisions in patients with metastatic castration resistant prostate cancer (mCRPC), the most advanced stage of prostate cancer. However, identifying mCRPC patients from administrative data is challenging and hinders researchers’ ability to assess testing among these patients. This study aims to develop algorithms using structured data and unstructured data with Natural language processing (NLP) methods to identify veterans by disease stage and hormone sensitivity, and to assess patient characteristics as well as receipt of tumor NGS testing.

Methods

We used biopsy, pathology, and diagnosis codes, to identify veterans with newly diagnosed PC within the Veterans Health Administration (VA) from January 1, 2017 to December 31, 2020. We developed and deployed: 1. A structured algorithm that used medication and Prostate-Specific Antigen (PSA) data to assess hormone sensitivity. 2. NLP tools to extract disease stage and hormone sensitivity from clinical notes. We report descriptive statistics on patient demographics, clinical characteristics, disease status, androgen deprivation therapy (ADT), and receipt of tumor NGS testing.

Results

There were 42,485 veterans with newly diagnosed prostate cancer between 2017-2020. This represented ~0.18% of veterans served in the VA and consisted of Whites (57%), Blacks (33%), and others (10%). During the study period, 3,113 (7.3%) patients had documentation of assessment for intraductal carcinoma, 5,160 (12.1%) had ADT treatment, 1,481 (3.5%) had CRPC, and 3,246 (7.6%) had metastatic disease. Among the 42,485 veterans, 422 received tumor NGS testing within VA, and 300 of them had metastatic disease. NLP tool and structured data algorithm collectively showed that 38% of the 422 tumor NGS testing recipients had mCRPC. Among all newly diagnosed PC patients, White patients had highest rates of tumor-based testing (2.3%), then Native Hawaiians (1.7%), Asians and Blacks (1.2% each), compared to Native Americans (0.4%).

Implications

NLP tools alongside structured data algorithms successfully identified variables required to measure access to tumor NGS testing. Efforts to validate and apply this method is ongoing to assess receipt of precision prostate cancer care in VA.

Purpose

Prostate cancer is the fifth leading cause of death in the United States. Genomic testing is essential to guide treatment decisions in patients with metastatic castration resistant prostate cancer (mCRPC), the most advanced stage of prostate cancer. However, identifying mCRPC patients from administrative data is challenging and hinders researchers’ ability to assess testing among these patients. This study aims to develop algorithms using structured data and unstructured data with Natural language processing (NLP) methods to identify veterans by disease stage and hormone sensitivity, and to assess patient characteristics as well as receipt of tumor NGS testing.

Methods

We used biopsy, pathology, and diagnosis codes, to identify veterans with newly diagnosed PC within the Veterans Health Administration (VA) from January 1, 2017 to December 31, 2020. We developed and deployed: 1. A structured algorithm that used medication and Prostate-Specific Antigen (PSA) data to assess hormone sensitivity. 2. NLP tools to extract disease stage and hormone sensitivity from clinical notes. We report descriptive statistics on patient demographics, clinical characteristics, disease status, androgen deprivation therapy (ADT), and receipt of tumor NGS testing.

Results

There were 42,485 veterans with newly diagnosed prostate cancer between 2017-2020. This represented ~0.18% of veterans served in the VA and consisted of Whites (57%), Blacks (33%), and others (10%). During the study period, 3,113 (7.3%) patients had documentation of assessment for intraductal carcinoma, 5,160 (12.1%) had ADT treatment, 1,481 (3.5%) had CRPC, and 3,246 (7.6%) had metastatic disease. Among the 42,485 veterans, 422 received tumor NGS testing within VA, and 300 of them had metastatic disease. NLP tool and structured data algorithm collectively showed that 38% of the 422 tumor NGS testing recipients had mCRPC. Among all newly diagnosed PC patients, White patients had highest rates of tumor-based testing (2.3%), then Native Hawaiians (1.7%), Asians and Blacks (1.2% each), compared to Native Americans (0.4%).

Implications

NLP tools alongside structured data algorithms successfully identified variables required to measure access to tumor NGS testing. Efforts to validate and apply this method is ongoing to assess receipt of precision prostate cancer care in VA.

Objective

To determine whether Black Veterans are at higher risk for prostate cancer diagnosis on their first prostate biopsy compared to non-Hispanic White (White) Veterans.

Background

Prostate-specific antigen (PSA) testing is widely used to screen for prostate cancer. Although men of African ancestry display an increased incidence of prostate cancer and more aggressive disease, specific PSA thresholds for biopsy referral have yet to be proposed for this population.

Methods

We used the VHA’s electronic medical record data to collect Veterans’ demographic and clinical characteristics including self-identified race/ethnicity, age, date of first prostate biopsy, PSA results, and prostate cancer diagnosis. Veterans’ ZIP code of residence was used to determine urban/rural status, income, and education. We estimated multivariable logistic regression models to predict the likelihood of prostate cancer diagnosis on the first biopsy using race, baseline PSA, age at first PSA test, age at initial biopsy, smoking status, use of statins, and socioeconomic factors as predictors. We calculated adjusted predicted probabilities of cancer detection on the first prostate biopsy from the logistic models at different PSA levels.

Results

We identified 246,056 White and 71,653 Black Veterans who underwent their first prostate biopsy through February 28, 2020 and who had no previous prostate cancer diagnosis or treatment prior to that biopsy. Black Veterans appeared to receive their first PSA test four years earlier and undergo their first prostate biopsy two years earlier than their White counterparts (median age of 57 vs. 61 and 63 vs. 65, respectively). After controlling for selected covariates, we found that Black Veterans were 52% more likely to be diagnosed with prostate cancer on their first prostate biopsy compared to White Veterans (OR 1.52, 95% CI 1.49-1.55). Our model indicated that a Black Veteran with a PSA of 4.0 ng/ml has an equivalent risk of prostate cancer detection as a White Veteran with a PSA of 9.7 ng/ml.

Implications

Our findings suggested that developing a risk-based PSA threshold for referral to prostate biopsy may lead to earlier diagnosis of clinically significant prostate cancer in a population of Veterans known to have an increased incidence and risk of aggressive disease.

Objective

To determine whether Black Veterans are at higher risk for prostate cancer diagnosis on their first prostate biopsy compared to non-Hispanic White (White) Veterans.

Background

Prostate-specific antigen (PSA) testing is widely used to screen for prostate cancer. Although men of African ancestry display an increased incidence of prostate cancer and more aggressive disease, specific PSA thresholds for biopsy referral have yet to be proposed for this population.

Methods

We used the VHA’s electronic medical record data to collect Veterans’ demographic and clinical characteristics including self-identified race/ethnicity, age, date of first prostate biopsy, PSA results, and prostate cancer diagnosis. Veterans’ ZIP code of residence was used to determine urban/rural status, income, and education. We estimated multivariable logistic regression models to predict the likelihood of prostate cancer diagnosis on the first biopsy using race, baseline PSA, age at first PSA test, age at initial biopsy, smoking status, use of statins, and socioeconomic factors as predictors. We calculated adjusted predicted probabilities of cancer detection on the first prostate biopsy from the logistic models at different PSA levels.

Results

We identified 246,056 White and 71,653 Black Veterans who underwent their first prostate biopsy through February 28, 2020 and who had no previous prostate cancer diagnosis or treatment prior to that biopsy. Black Veterans appeared to receive their first PSA test four years earlier and undergo their first prostate biopsy two years earlier than their White counterparts (median age of 57 vs. 61 and 63 vs. 65, respectively). After controlling for selected covariates, we found that Black Veterans were 52% more likely to be diagnosed with prostate cancer on their first prostate biopsy compared to White Veterans (OR 1.52, 95% CI 1.49-1.55). Our model indicated that a Black Veteran with a PSA of 4.0 ng/ml has an equivalent risk of prostate cancer detection as a White Veteran with a PSA of 9.7 ng/ml.

Implications

Our findings suggested that developing a risk-based PSA threshold for referral to prostate biopsy may lead to earlier diagnosis of clinically significant prostate cancer in a population of Veterans known to have an increased incidence and risk of aggressive disease.

Objective

To determine whether Black Veterans are at higher risk for prostate cancer diagnosis on their first prostate biopsy compared to non-Hispanic White (White) Veterans.

Background

Prostate-specific antigen (PSA) testing is widely used to screen for prostate cancer. Although men of African ancestry display an increased incidence of prostate cancer and more aggressive disease, specific PSA thresholds for biopsy referral have yet to be proposed for this population.

Methods

We used the VHA’s electronic medical record data to collect Veterans’ demographic and clinical characteristics including self-identified race/ethnicity, age, date of first prostate biopsy, PSA results, and prostate cancer diagnosis. Veterans’ ZIP code of residence was used to determine urban/rural status, income, and education. We estimated multivariable logistic regression models to predict the likelihood of prostate cancer diagnosis on the first biopsy using race, baseline PSA, age at first PSA test, age at initial biopsy, smoking status, use of statins, and socioeconomic factors as predictors. We calculated adjusted predicted probabilities of cancer detection on the first prostate biopsy from the logistic models at different PSA levels.

Results

We identified 246,056 White and 71,653 Black Veterans who underwent their first prostate biopsy through February 28, 2020 and who had no previous prostate cancer diagnosis or treatment prior to that biopsy. Black Veterans appeared to receive their first PSA test four years earlier and undergo their first prostate biopsy two years earlier than their White counterparts (median age of 57 vs. 61 and 63 vs. 65, respectively). After controlling for selected covariates, we found that Black Veterans were 52% more likely to be diagnosed with prostate cancer on their first prostate biopsy compared to White Veterans (OR 1.52, 95% CI 1.49-1.55). Our model indicated that a Black Veteran with a PSA of 4.0 ng/ml has an equivalent risk of prostate cancer detection as a White Veteran with a PSA of 9.7 ng/ml.

Implications

Our findings suggested that developing a risk-based PSA threshold for referral to prostate biopsy may lead to earlier diagnosis of clinically significant prostate cancer in a population of Veterans known to have an increased incidence and risk of aggressive disease.