Agent orange exposure and prostate cancer risk in the million veteran program.

BACKGROUND: The US government considers veterans to have been exposed to Agent Orange if they served in Vietnam while the carcinogen was in use, and these veterans are often deemed at high risk of prostate cancer (PCa). Here, we assess whether presumed Agent Orange exposure is independently associated with increased risk of any metastatic or fatal PCa in a diverse Veteran cohort still alive in the modern era (at least 2011), when accounting for race/ethnicity, family history, and genetic risk. PATIENTS AND METHODS: Participants in the Million Veteran Program (MVP; enrollment began in 2011) who were on active duty during the Vietnam War era (August 1964-April 1975) were included (n = 301,470). Agent Orange exposure was determined using the US government definition. Genetic risk was assessed via a validated polygenic hazard score. Associations with age at diagnosis of any PCa, metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. RESULTS AND INTERPRETATION: On univariable analysis, exposure to Agent Orange was not associated with increased PCa (hazard ratio [HR]: 1.02, 95% confidence interval [CI]: 1.00-1.04, p = 0.06), metastatic PCa (HR: 0.98, 95% CI: 0.91-1.05, p = 0.55), or fatal PCa (HR: 0.94, 95% CI: 0.79-1.09, p = 0.41). When accounting for race/ethnicity and family history, Agent Orange exposure was independently associated with slightly increased risk of PCa (HR: 1.06, 95% CI: 1.04-1.09, <10-6) but not with metastatic PCa (HR: 1.07, 95% CI: 0.98-1.15, p = 0.10) or PCa death (HR: 1.02, 95% CI: 0.83-1.23, p = 0.09). Similar results were found when accounting for genetic risk. Agent Orange exposure history may not improve modern PCa risk stratification.

Genetic risk and likelihood of prostate cancer detection on first biopsy by ancestry.

Despite differences in prostate cancer risk across ancestry groups, relative performance of prostate cancer genetic risks scores (GRS) for positive biopsy prediction in different ancestry groups is unknown. This cross-sectional retrospective analysis examines the association between a polygenic hazard score (PHS290) and risk of prostate cancer diagnosis upon first biopsy in male veterans using 2-sided tests. Our analysis included 36 717 veterans (10 297 of African ancestry). Unadjusted rates of positive first prostate biopsy increased with higher genetic risk (low risk: 34%, high risk: 58%; P < .001). Among men of African ancestry, higher genetic risk was associated with increased prostate cancer detection on first biopsy (odds ratio = 2.18, 95% confidence interval = 1.93 to 2.47), but the effect was stronger among men of European descent (odds ratio = 3.89, 95% confidence interval = 3.62 to 4.18). These findings suggest that incorporating genetic risk into prediction models could better personalize biopsy decisions, although further study is needed to achieve equitable genetic risk stratification among ancestry groups.

An NLP Framework for the Extraction of Concept Measurements from Radiology and Pathology Notes.

Natural language processing (NLP) tools can automate the identification of cancer patients eligible for specific pathways. We developed and validated a cancer agnostic, rules-based NLP framework to extract the dimensions and measurements of several concepts from pathology and radiology reports. This framework was then efficiently and cost-effectively deployed to identify patients eligible for breast, lung, and prostate cancers clinical pathways.

Development of a Natural Language Processing System to Identify Clinical Documentation of Electronic Cigarette Use.

Electronic Nicotine Delivery Systems (ENDS) use has increased substantially in the United States since 2010. To date, there is limited evidence regarding the nature and extent of ENDS documentation in the clinical note. In this work we investigate the effectiveness of different approaches to identify a patient's documented ENDS use. We report on the development and validation of a natural language processing system to identify patients with explicit documentation of ENDS using a large national cohort of patients at the United States Department of Veterans Affairs.

Association between prediagnostic prostate-specific antigen and prostate cancer probability in Black and non-Hispanic White men.

BACKGROUND: Although Black men are more likely than non-Hispanic White men to develop and die from prostate cancer, limited data exist to guide prostate-specific antigen (PSA) screening protocols in Black men. This study investigated whether the risk for prostate cancer was higher than expected among self-identified Black than White veterans based on prebiopsy PSA level. METHODS: Multivariable logistic regression models were estimated to predict the likelihood of prostate cancer diagnosis on first biopsy for 75,295 Black and 207,658 White male veterans. Self-identified race, age at first PSA test, prebiopsy PSA, age at first biopsy, smoking status, statin use, and socioeconomic factors were used as predictors. The adjusted predicted probabilities of cancer detection on first prostate biopsy from the logistic models at different PSA levels were calculated. RESULTS: After controlling for PSA and other covariates, Black veterans were 50% more likely to receive a prostate cancer diagnosis on their first prostate biopsy than White veterans (odds ratio [OR], 1.50; 95% CI, 1.47-1.53; p < .001). At a PSA level of 4.0 ng/mL, the probability of prostate cancer for a Black man was 49% compared with 39% for a White man. This model indicated that Black veterans with a PSA of 4.0 ng/mL have an equivalent risk of prostate cancer as White veterans with a PSA of 13.4 ng/mL. CONCLUSIONS: The findings indicate that, at any given PSA level, Black men are more likely to harbor prostate cancer than White men. Prospective studies are needed to better evaluate risks and benefits of PSA screening in Black men and other high-risk populations.

Development and Validation of a Tool to Identify Patients Diagnosed With Castration-Resistant Prostate Cancer.

PURPOSE: Several novel therapies for castration-resistant prostate cancer (CRPC) have been approved with randomized phase III studies with continuing observational research either planned or ongoing. Accurately identifying patients with CRPC in electronic health care data is critical for quality observational research, resource allocation, and quality improvement. Previous work in this area has relied on either structured laboratory results and medication data or natural language processing (NLP) methods. However, a computable phenotype using both structured data and NLP identifies these patients with more accuracy. METHODS: The Corporate Data Warehouse (CDW) of the Veterans Health Administration (VHA) was used to collect PCa diagnoses, prostate-specific antigen test results, and information regarding patient characteristics and medication use. The final system used for validation and subsequent analysis combined the NLP system and an algorithm of structured laboratory and medication data to identify patients as being diagnosed with CRPC. Patients with both a documented diagnosis of CRPC and a documented diagnosis of metastatic PCa were classified as having mCRPC by this system. RESULTS: Among 1.2 million veterans with PCa, the International Classification of Diseases (ICD)-10 diagnosis code for CRPC (Z19.2) identifies 3,791 patients from 2016 when the code was created until 2022, compared with the combined algorithm which identifies 14,103, 10,312 more than ICD-10 codes alone, from 2016 to 2022. The combined algorithm showed a sensitivity of 97.9% and a specificity of 99.2%. CONCLUSION: ICD-10 codes proved to be insufficient for capturing CRPC in the VHA CDW data. Using both structured and unstructured data identified more than double the number of patients compared with ICD-10 codes alone. Application of this combined approach drastically improved identification of real-world patients and enables high-quality observational research in mCRPC.

Agent Orange exposure and prostate cancer risk in the Million Veteran Program.

Purpose: Exposure to Agent Orange, a known carcinogen, might increase risk of prostate cancer (PCa). We sought to investigate the association of Agent Orange exposure and PCa risk when accounting for race/ethnicity, family history, and genetic risk in a diverse population of US Vietnam War veterans. Methods & Materials: This study utilized the Million Veteran Program (MVP), a national, population-based cohort study of United States military veterans conducted 2011-2021 with 590,750 male participants available for analysis. Agent Orange exposure was obtained using records from the Department of Veterans Affairs (VA) using the US government definition of Agent Orange exposure: active service in Vietnam while Agent Orange was in use. Only veterans who were on active duty (anywhere in the world) during the Vietnam War were included in this analysis (211,180 participants). Genetic risk was assessed via a previously validated polygenic hazard score calculated from genotype data. Age at diagnosis of any PCa, diagnosis of metastatic PCa, and death from PCa were assessed via Cox proportional hazards models. Results: Exposure to Agent Orange was associated with increased PCa diagnosis (HR 1.04, 95% CI 1.01-1.06, p=0.003), primarily among Non-Hispanic White men (HR 1.09, 95% CI 1.06- 1.12, p<0.001). When accounting for race/ethnicity and family history, Agent Orange exposure remained an independent risk factor for PCa diagnosis (HR 1.06, 95% CI 1.04-1.09, p<0.05). Univariable associations of Agent Orange exposure with PCa metastasis (HR 1.08, 95% CI 0.99-1.17) and PCa death (HR 1.02, 95% CI 0.84-1.22) did not reach significance on multivariable analysis. Similar results were found when accounting for polygenic hazard score. Conclusions: Among US Vietnam War veterans, Agent Orange exposure is an independent risk factor for PCa diagnosis, though associations with PCa metastasis or death are unclear when accounting for race/ethnicity, family history, and/or polygenic risk.

Tumor testing and treatment patterns in veterans with metastatic castration-resistant prostate cancer.

INTRODUCTION: In 2016, the Department of Veterans Affairs (VA) and Prostate Cancer Foundation (PCF) began a partnership to improve access to testing. The primary objective of this analysis was to describe the use of tumor testing and treatment patterns in Veterans who progressed to metastatic castration-resistant prostate cancer (mCRPC) from 2016 to 2021. Secondary objectives including identifying factors associated with receipt of tumor testing, and reporting HRR mutation results among a subset who were tested. METHODS AND MATERIALS: Natural language processing algorithms were applied to VA electronic health record data to identify a nationwide cohort of veterans with mCRPC. Tumor testing over time and by region were reported, alongside first-, second-, and third-line treatment patterns. Factors associated with receipt of tumor testing were identified using generalized linear mixed models with binomial distributions and logit links to account for clustering by VA facility. RESULTS: Of the 9,852 veterans analyzed, 1,972 (20%) received tumor testing, with 73% of testing occurring in 2020-2021. Factors associated with tumor testing included younger age, later diagnosis year, being treated in the Midwest, or Puerto Rico or other compared to the South, and being treated at a PCF-VA Center of Excellence. Fifteen percent of tests were positive for a pathogenic HRR mutation. Seventy-six percent of the study cohort received first-line treatment, and among those, a subsequent 52% received second-line treatment. A subsequent 46% received third-line treatment. CONCLUSION: After the VA-PCF partnership, one-fifth of veterans with mCRPC received tumor testing, with most tests occurring in 2020-2021.

Actionable Genomic Alterations in Prostate Cancer Among Black and White United States Veterans.

Black Veterans have higher a incidence of localized and metastatic prostate cancer compared to White Veterans yet are underrepresented in reports of frequencies of somatic and germline alterations. This retrospective analysis of somatic and putative germline alterations was conducted in a large cohort of Veterans with prostate cancer (N = 835 Black, 1613 White) who underwent next generation sequencing through the VA Precision Oncology Program, which facilitates molecular testing for Veterans with metastatic cancer. No differences were observed in gene alterations for FDA approved targetable therapies (13.5% in Black Veterans vs. 15.5% in White Veterans, P = .21), nor in any potentially actionable alterations (25.5% vs. 28.7%, P =.1). Black Veterans had higher rates of BRAF (5.5% vs. 2.6%, P < .001) alterations, White Veterans TMPRSS2 fusions (27.2% vs. 11.7%, P < .0001). Putative germline alteration rates were higher in White Veterans (12.0% vs. 6.1%, P < .0001). Racial disparities in outcome are unlikely attributable to acquired somatic alterations in actionable pathways.

Association of Sex and Race With Incident Peripheral Artery Disease Among Veterans With Normal Ankle-Brachial Indices.

Importance: Reported risk of incident peripheral artery disease (PAD) by sex and race varies significantly and has not been reported in national cohorts among individuals free of baseline PAD. Objective: To evaluate the association of sex and race, as well as prevalent cardiovascular risk factors, with limb outcomes in a national cohort of people with normal baseline ankle-brachial indices (ABIs). Design, setting, and participants: This cohort study was conducted using data from participants in the Veterans Affairs Birth Cohort Study (born 1945-1965), with follow-up data between January 1, 2000, and December 31, 2016. Baseline demographics were collected from 77 041 participants receiving care from the Veterans Health Administration with baseline ABIs of 0.90 to 1.40 and no history of PAD. Data were analyzed from October 2019 through September 2022. Exposures: Sex, race, diabetes, and smoking status. Main Outcomes and Measures: Incident PAD, defined as subsequent ABI less than 0.90, surgical or percutaneous revascularization, or nontraumatic amputation. Results: Of 77 041 participants with normal ABIs (73 822 [95.8%] men; mean [SD] age, 60.2 [5.9] years; 13 080 Black [18.2%] and 54 377 White [75.6%] among 71 911 participants with race and ethnicity data), there were 6692 incident PAD events over a median [IQR] of 3.9 [1.7-6.9] years. Incidence rates were lower for women than men (incidence rates [IRs] per 1000 person-years, 7.4 incidents [95% CI, 6.2-8.8 incidents] vs 19.2 incidents [95% CI, 18.7-19.6 incidents]), with a lower risk of incident PAD (adjusted hazard ratio [aHR], 0.49 [95% CI, 0.41-0.59]). IRs per 1000 person-years of incident PAD were similar for Black and White participants (18.9 incidents [95% CI, 17.9-20.1 incidents] vs 18.8 incidents [95% CI, 18.3-19.4]). Compared with White participants, Black participants had increased risk of total PAD (aHR, 1.09 [95% CI, 1.02-1.16]) and nontraumatic amputation (aHR, 1.20 [95% CI, 1.06-1.36]) but not surgical or percutaneous revascularization (aHR, 1.10 [95% CI, 0.98-1.23]) or subsequent ABI less than 0.90 (aHR, 1.04 [95% CI, 0.95-1.13]). Diabetes (aHR, 1.62 [95% CI, 1.53-1.72]) and smoking (eg, current vs never: aHR, 1.76 [95% CI, 1.64-1.89]) were associated with incident PAD. Incident PAD was rare among individuals without a history of smoking or diabetes (eg, among 632 women: IR per 1000 people-years, 2.1 incidents [95% CI, 1.0-4.5 incidents]) despite an otherwise-high-risk cardiovascular profile (eg, 527 women [83.4%] with hypertension). Conclusions and Relevance: This study found that the risk of PAD was approximately 50% lower in women than men and less than 10% higher for Black vs White participants, while the risk of nontraumatic amputation was 20% higher among Black compared with White participants.

Association of Prostate-Specific Antigen Screening Rates With Subsequent Metastatic Prostate Cancer Incidence at US Veterans Health Administration Facilities.

Importance: There is controversy about the benefit of prostate-specific antigen (PSA) screening. Prostate-specific antigen screening rates have decreased since 2008 in the US, and the incidence of metastatic prostate cancer has increased. However, there is no direct epidemiologic evidence of a correlation between population PSA screening rates and subsequent metastatic prostate cancer rates. Objective: To assess whether facility-level variation in PSA screening rates is associated with subsequent facility-level metastatic prostate cancer incidence. Design, Setting, and Participants: This retrospective cohort used data for all men aged 40 years or older with an encounter at 128 facilities in the US Veterans Health Administration (VHA) from January 1, 2005, to December 31, 2019. Exposures: Yearly facility-level PSA screening rates, defined as the proportion of men aged 40 years or older with a PSA test in each year, and long-term nonscreening rates, defined as the proportion of men aged 40 years or older without a PSA test in the prior 3 years, from January 1, 2005, to December 31, 2014. Main Outcomes and Measures: The main outcomes were facility-level yearly counts of incident metastatic prostate cancer diagnoses and age-adjusted yearly metastatic prostate cancer incidence rates (per 100 000 men) 5 years after each PSA screening exposure year. Results: The cohort included 4 678 412 men in 2005 and 5 371 701 men in 2019. Prostate-specific antigen screening rates decreased from 47.2% in 2005 to 37.0% in 2019, and metastatic prostate cancer incidence increased from 5.2 per 100 000 men in 2005 to 7.9 per 100 000 men in 2019. Higher facility-level PSA screening rates were associated with lower metastatic prostate cancer incidence 5 years later (incidence rate ratio [IRR], 0.91 per 10% increase in PSA screening rate; 95% CI, 0.87-0.96; P < .001). Higher long-term nonscreening rates were associated with higher metastatic prostate cancer incidence 5 years later (IRR, 1.11 per 10% increase in long-term nonscreening rate; 95% CI, 1.03-1.19; P = .01). Conclusions and Relevance: From 2005 to 2019, PSA screening rates decreased in the national VHA system. Facilities with higher PSA screening rates had lower subsequent rates of metastatic prostate cancer. These data may be used to inform shared decision-making about the potential benefits of PSA screening among men who wish to reduce their risk of metastatic prostate cancer.

A Population-Level Analysis of the Protective Effects of Androgen Deprivation Therapy Against COVID-19 Disease Incidence and Severity.

Background: The incidence and severity of coronavirus disease 19 (COVID-19) is substantially higher in men. Sex hormones may be a potential mechanism for differences in COVID-19 outcome in men and women. We hypothesized that men treated with androgen deprivation therapy (ADT) have lower incidence and severity of COVID-19. Methods: We conducted an observational study of male Veterans treated in the Veterans Health Administration from February 15th to July 15th, 2020. We developed a propensity score model to predict the likelihood to undergo Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) testing. We performed multivariable logistic regression modeling adjusted with inverse probability weighting to examine the relationship between ADT and COVID-19 incidence. We conducted logistic regression analysis among COVID-19 patients to test the association between ADT and COVID-19 severity. Results: We identified a large cohort of 246,087 VA male patients who had been tested for SARS-CoV-2, of whom 3,057 men were exposed to ADT, and 36,096 men with cancer without ADT. Of these, 295 ADT patients and 2,427 cancer patients not on ADT had severe COVID-19 illness. In the primary, propensity-weighted comparison of ADT patients to cancer patients not on ADT, ADT was associated with decreased likelihood of testing positive for SARS-CoV-2 (adjusted OR, 0.88 [95% CI, 0.81-0.95]; p = 0.001). Furthermore, ADT was associated with fewer severe COVID-19 outcomes (OR 0.72 [95% CI 0.53-0.96]; p = 0.03). Conclusion: ADT is associated with reduced incidence and severity of COVID-19 amongst male Veterans. Testosterone and androgen receptor signaling may confer increased risk for SARS-CoV-2 infection and contribute to severe COVID-19 pathophysiology in men.

Demographic Differences Among US Department of Veterans Affairs Patients Referred for Genetic Consultation to a Centralized VA Telehealth Program, VA Medical Centers, or the Community.

Importance: Telehealth enables access to genetics clinicians, but impact on care coordination is unknown. Objective: To assess care coordination and equity of genetic care delivered by centralized telehealth and traditional genetic care models. Design, Setting, and Participants: This cross-sectional study included patients referred for genetic consultation from 2010 to 2017 with 2 years of follow-up in the US Department of Veterans Affairs (VA) health care system. Patients were excluded if they were referred for research, cytogenetic, or infectious disease testing, or if their care model could not be determined. Exposures: Genetic care models, which included VA-telehealth (ie, a centralized team of genetic counselors serving VA facilities nationwide), VA-traditional (ie, a regional service by clinical geneticists and genetic counselors), and non-VA care (ie, community care purchased by the VA). Main Outcomes and Measures: Multivariate regression models were used to assess associations between patient and consultation characteristics and the type of genetic care model referral; consultation completion; and having 0, 1, or 2 or more cancer surveillance (eg, colonoscopy) and risk-reducing procedures (eg, bilateral mastectomy) within 2 years following referral. Results: In this study, 24 778 patients with genetics referrals were identified, including 12 671 women (51.1%), 13 193 patients aged 50 years or older (53.2%), 15 639 White patients (63.1%), and 15 438 patients with cancer-related referrals (62.3%). The VA-telehealth model received 14 580 of the 24 778 consultations (58.8%). Asian patients, American Indian or Alaskan Native patients, and Hawaiian or Pacific Islander patients were less likely to be referred to VA-telehealth than White patients (OR, 0.54; 95% CI, 0.35-0.84) compared with the VA-traditional model. Completing consultations was less likely with non-VA care than the VA-traditional model (OR, 0.45; 95% CI, 0.35-0.57); there were no differences in completing consultations between the VA models. Black patients were less likely to complete consultations than White patients (OR, 0.84; 95% CI, 0.76-0.93), but only if referred to the VA-telehealth model. Patients were more likely to have multiple cancer preventive procedures if they completed their consultations (OR, 1.55; 95% CI, 1.40-1.72) but only if their consultations were completed with the VA-traditional model. Conclusions and Relevance: In this cross-sectional study, the VA-telehealth model was associated with improved access to genetics clinicians but also with exacerbated health care disparities and hindered care coordination. Addressing structural barriers and the needs and preferences of vulnerable subpopulations may complement the centralized telehealth approach, improve care coordination, and help mitigate health care disparities.

Clinician documentation of patient centered care in the electronic health record.

BACKGROUND: In this study we sought to explore the possibility of using patient centered care (PCC) documentation as a measure of the delivery of PCC in a health system. METHODS: We first selected 6 VA medical centers based on their scores for a measure of support for self-management subscale from a national patient satisfaction survey (the Survey for Healthcare Experience-Patients). We accessed clinical notes related to either smoking cessation or weight management consults. We then annotated this dataset of notes for documentation of PCC concepts including: patient goals, provider support for goal progress, social context, shared decision making, mention of caregivers, and use of the patient's voice. We examined the association of documentation of PCC with patients' perception of support for self-management with regression analyses. RESULTS: Two health centers had < 50 notes related to either tobacco cessation or weight management consults and were removed from further analysis. The resulting dataset includes 477 notes related to 311 patients total from 4 medical centers. For a majority of patients (201 out of 311; 64.8%) at least one PCC concept was present in their clinical notes. The most common PCC concepts documented were patient goals (patients n = 126; 63% clinical notes n = 302; 63%), patient voice (patients n = 165, 82%; clinical notes n = 323, 68%), social context (patients n = 105, 52%; clinical notes n = 181, 38%), and provider support for goal progress (patients n = 124, 62%; clinical notes n = 191, 40%). Documentation of goals for weight loss notes was greater at health centers with higher satisfaction scores compared to low. No such relationship was found for notes related to tobacco cessation. CONCLUSION: Providers document PCC concepts in their clinical notes. In this pilot study we explored the feasibility of using this data as a means to measure the degree to which care in a health center is patient centered. PRACTICE IMPLICATIONS: clinical EHR notes are a rich source of information about PCC that could potentially be used to assess PCC over time and across systems with scalable technologies such as natural language processing.

Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network.

BACKGROUND: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. METHODS: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. RESULTS: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. CONCLUSIONS: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use.

Racial and Ethnic Disparities in Prostate Cancer Outcomes in the Veterans Affairs Health Care System.

Importance: Prostate cancer (PCa) disproportionately affects African American men, but research evaluating the extent of racial and ethnic disparities across the PCa continuum in equal-access settings remains limited at the national level. The US Department of Veterans Affairs (VA) Veterans Hospital Administration health care system offers a setting of relatively equal access to care in which to assess racial and ethnic disparities in self-identified African American (or Black) veterans and White veterans. Objective: To determine the extent of racial and ethnic disparities in the incidence of PCa, clinical stage, and outcomes between African American patients and White patients who received a diagnosis or were treated at a VA hospital. Design, Setting, and Participants: This retrospective cohort study included 7 889 984 veterans undergoing routine care in VA hospitals nationwide from 2005 through 2019 (incidence cohort). The age-adjusted incidence of localized and de novo metastatic PCa was estimated. Treatment response was evaluated, and PCa-specific outcomes were compared between African American veterans and White veterans. Residual disparity in PCa outcome, defined as the leftover racial and ethnic disparity in the outcomes despite equal response to treatment, was estimated. Exposures: Self-identified African American (or Black) and White race and ethnicity. Main Outcomes and Measures: Time to distant metastasis following PCa diagnosis was the primary outcome. Descriptive analyses were used to compare baseline demographics and clinic characteristics. Multivariable logistic regression was used to evaluate race and ethnicity association with pretreatment clinical variables. Multivariable Cox regression was used to estimate the risk of metastasis. Results: Data from 7 889 984 veterans from the incidence cohort were used to estimate incidence, whereas data from 92 269 veterans with localized PCa were used to assess treatment response. Among 92 269 veterans, African American men (n = 28 802 [31%]) were younger (median [IQR], 63 [58-68] vs 65 [62-71] years) and had higher prostate-specific antigen levels (>20 ng/mL) at the time of diagnosis compared with White men (n = 63 467; [69%]). Consistent with US population-level data, African American veterans displayed a nearly 2-fold greater incidence of localized and de novo metastatic PCa compared with White men across VA centers nationwide. Among veterans screened for PCa, African American men had a 29% increased risk of PCa detection on a diagnostic prostate biopsy compared with White (hazard ratio, 1.29; 95% CI, 1.27-1.31; P < .001). African American men who received definitive primary treatment of PCa experienced a lower risk of metastasis (hazard ratio, 0.89; 95% CI, 0.83-0.95; P < .001). However, African American men who received nondefinitive treatment classified as "other" were more likely to develop metastasis (adjusted hazard ratio, 1.29; 95% CI, 1.17-1.42; P < .001). Using the actual rate of metastasis from veterans who received definitive primary treatment, a persistent residual metastatic burden for African American men was observed across all National Comprehensive Cancer Network risk groups (low risk, 4 vs 2 per 100 000; intermediate risk, 13 vs 6 per 100 000; high risk, 19 vs 9 per 100 000). Conclusions and Relevance: This cohort analysis found significant disparities in the incidence of localized and metastatic PCa between African American veterans and White veterans. This increased incidence is a major factor associated with the residual disparity in PCa metastasis observed in African American veterans compared with White veterans despite their nearly equal response to treatment.

Identifying Posttraumatic Stress Disorder and Disparity Among Transgender Veterans Using Nationwide Veterans Health Administration Electronic Health Record Data.

Purpose: The prevalence of posttraumatic stress disorder (PTSD) and other psychiatric disorders is high among military veterans and even higher among transgender veterans. Prior prevalence estimates have become outdated, and novel methods of estimation have since been developed but not used to estimate PTSD prevalence among transgender veterans. This study provides updated estimates of PTSD prevalence among transgender and cisgender veterans. Methods: We examined Veterans Health Administration (VHA) medical record data from October 1, 1999 to April 1, 2021 for 9995 transgender veterans and 29,985 cisgender veteran comparisons (1:3). We matched on age group at first VHA health care visit, sex assigned at birth, and year of first VHA visit. We employed both probabilistic and rule-based algorithms to estimate the prevalence of PTSD for transgender and cisgender veterans. Results: The prevalence of PTSD was 1.5-1.8 times higher among transgender veterans. Descriptive data suggest that the prevalence of depression, schizophrenia, bipolar disorder, alcohol and non-alcohol substance use disorders, current/former smoking status, and military sexual trauma was also elevated among transgender veterans. Conclusion: The PTSD and overall psychiatric burden observed among transgender veterans was significantly higher than that of their cisgender peers, especially among recent users of VHA care. These PTSD findings are consistent with prior literature and minority stress theory, and they were robust across probabilistic and two rule-based methods employed in this study. As such, enhanced and careful screening, outreach, and evidence-based practices are recommended to help reduce this disparity among transgender veterans.

ProjectFlow: a configurable workflow management application for point of care research.

OBJECTIVE: To best meet our point-of-care research (POC-R) needs, we developed ProjectFlow, a configurable, clinical research workflow management application. In this article, we describe ProjectFlow and how it is used to manage study processes for the Diuretic Comparison Project (DCP) and the Research Precision Oncology Program (RePOP). MATERIALS AND METHODS: The Veterans Health Administration (VHA) is the largest integrated health care system in the United States. ProjectFlow is a flexible web-based workflow management tool specifically created to facilitate conduct of our clinical research initiatives within the VHA. The application was developed using the Grails web framework and allows researchers to create custom workflows using Business Process Model and Notation. RESULTS: As of January 2021, ProjectFlow has facilitated management of study recruitment, enrollment, randomization, and drug orders for over 10 000 patients for the DCP clinical trial. It has also helped us evaluate over 3800 patients for recruitment and enroll over 370 of them into RePOP for use in data sharing partnerships and predictive analytics aimed at optimizing cancer treatment in the VHA. DISCUSSION: The POC-R study design embeds research processes within day-to-day clinical care and leverages longitudinal electronic health record (EHR) data for study recruitment, monitoring, and outcome reporting. Software that allows flexibility in study workflow creation and integrates with enterprise EHR systems is critical to the success of POC-R. CONCLUSIONS: We developed a flexible web-based informatics solution called ProjectFlow that supports custom research workflow configuration and has ability to integrate data from existing VHA EHR systems.

Ascertainment of Veterans With Metastatic Prostate Cancer in Electronic Health Records: Demonstrating the Case for Natural Language Processing.

PURPOSE: Prostate cancer (PCa) is among the leading causes of cancer deaths. While localized PCa has a 5-year survival rate approaching 100%, this rate drops to 31% for metastatic prostate cancer (mPCa). Thus, timely identification of mPCa is a crucial step toward measuring and improving access to innovations that reduce PCa mortality. Yet, methods to identify patients diagnosed with mPCa remain elusive. Cancer registries provide detailed data at diagnosis but are not updated throughout treatment. This study reports on the development and validation of a natural language processing (NLP) algorithm deployed on oncology, urology, and radiology clinical notes to identify patients with a diagnosis or history of mPCa in the Department of Veterans Affairs. PATIENTS AND METHODS: Using a broad set of diagnosis and histology codes, the Veterans Affairs Corporate Data Warehouse was queried to identify all Veterans with PCa. An NLP algorithm was developed to identify patients with any history or progression of mPCa. The NLP algorithm was prototyped and developed iteratively using patient notes, grouped into development, training, and validation subsets. RESULTS: A total of 1,144,610 Veterans were diagnosed with PCa between January 2000 and October 2020, among which 76,082 (6.6%) were identified by NLP as having mPCa at some point during their care. The NLP system performed with a specificity of 0.979 and sensitivity of 0.919. CONCLUSION: Clinical documentation of mPCa is highly reliable. NLP can be leveraged to improve PCa data. When compared to other methods, NLP identified a significantly greater number of patients. NLP can be used to augment cancer registry data, facilitate research inquiries, and identify patients who may benefit from innovations in mPCa treatment.

Characteristics and Outcomes of Over 300,000 Patients with COVID-19 and History of Cancer in the United States and Spain.

BACKGROUND: We described the demographics, cancer subtypes, comorbidities, and outcomes of patients with a history of cancer and coronavirus disease 2019 (COVID-19). Second, we compared patients hospitalized with COVID-19 to patients diagnosed with COVID-19 and patients hospitalized with influenza. METHODS: We conducted a cohort study using eight routinely collected health care databases from Spain and the United States, standardized to the Observational Medical Outcome Partnership common data model. Three cohorts of patients with a history of cancer were included: (i) diagnosed with COVID-19, (ii) hospitalized with COVID-19, and (iii) hospitalized with influenza in 2017 to 2018. Patients were followed from index date to 30 days or death. We reported demographics, cancer subtypes, comorbidities, and 30-day outcomes. RESULTS: We included 366,050 and 119,597 patients diagnosed and hospitalized with COVID-19, respectively. Prostate and breast cancers were the most frequent cancers (range: 5%-18% and 1%-14% in the diagnosed cohort, respectively). Hematologic malignancies were also frequent, with non-Hodgkin's lymphoma being among the five most common cancer subtypes in the diagnosed cohort. Overall, patients were aged above 65 years and had multiple comorbidities. Occurrence of death ranged from 2% to 14% and from 6% to 26% in the diagnosed and hospitalized COVID-19 cohorts, respectively. Patients hospitalized with influenza (n = 67,743) had a similar distribution of cancer subtypes, sex, age, and comorbidities but lower occurrence of adverse events. CONCLUSIONS: Patients with a history of cancer and COVID-19 had multiple comorbidities and a high occurrence of COVID-19-related events. Hematologic malignancies were frequent. IMPACT: This study provides epidemiologic characteristics that can inform clinical care and etiologic studies.