Chlorthalidone vs. Hydrochlorothiazide for Hypertension-Cardiovascular Events.

BACKGROUND: Whether chlorthalidone is superior to hydrochlorothiazide for preventing major adverse cardiovascular events in patients with hypertension is unclear. METHODS: In a pragmatic trial, we randomly assigned adults 65 years of age or older who were patients in the Department of Veterans Affairs health system and had been receiving hydrochlorothiazide at a daily dose of 25 or 50 mg to continue therapy with hydrochlorothiazide or to switch to chlorthalidone at a daily dose of 12.5 or 25 mg. The primary outcome was a composite of nonfatal myocardial infarction, stroke, heart failure resulting in hospitalization, urgent coronary revascularization for unstable angina, and non-cancer-related death. Safety was also assessed. RESULTS: A total of 13,523 patients underwent randomization. The mean age was 72 years. At baseline, hydrochlorothiazide at a dose of 25 mg per day had been prescribed in 12,781 patients (94.5%). The mean baseline systolic blood pressure in each group was 139 mm Hg. At a median follow-up of 2.4 years, there was little difference in the occurrence of primary-outcome events between the chlorthalidone group (702 patients [10.4%]) and the hydrochlorothiazide group (675 patients [10.0%]) (hazard ratio, 1.04; 95% confidence interval, 0.94 to 1.16; P = 0.45). There were no between-group differences in the occurrence of any of the components of the primary outcome. The incidence of hypokalemia was higher in the chlorthalidone group than in the hydrochlorothiazide group (6.0% vs. 4.4%, P<0.001). CONCLUSIONS: In this large pragmatic trial of thiazide diuretics at doses commonly used in clinical practice, patients who received chlorthalidone did not have a lower occurrence of major cardiovascular outcome events or non-cancer-related deaths than patients who received hydrochlorothiazide. (Funded by the Veterans Affairs Cooperative Studies Program; ClinicalTrials.gov number, NCT02185417.).

The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer.

PURPOSE: In advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitor (ICI) monotherapy is often preferred over intensive ICI treatment for frail patients and those with poor performance status (PS). Among those with poor PS, the additional effect of frailty on treatment selection and mortality is unknown. METHODS: Patients in the veterans affairs national precision oncology program from 1/2019-12/2021 who received first-line ICI for advanced NSCLC were followed until death or study end 6/2022. Association of an electronic frailty index with treatment selection was examined using logistic regression stratified by PS. We also examined overall survival (OS) on intensive treatment using Cox regression stratified by PS. Intensive treatment was defined as concurrent use of platinum-doublet chemotherapy and/or dual checkpoint blockade and non-intensive as ICI monotherapy. RESULTS: Of 1547 patients receiving any ICI, 66.2% were frail, 33.8% had poor PS (≥ 2), and 25.8% were both. Frail patients received less intensive treatment than non-frail patients in both PS subgroups (Good PS: odds ratio [OR] 0.67, 95% confidence interval [CI] 0.51 - 0.88; Poor PS: OR 0.69, 95% CI 0.44 - 1.10). Among 731 patients receiving intensive treatment, frailty was associated with lower OS for those with good PS (hazard ratio [HR] 1.53, 95% CI 1.2 - 1.96), but no association was observed with poor PS (HR 1.03, 95% CI 0.67 - 1.58). CONCLUSION: Frail patients with both good and poor PS received less intensive treatment. However, frailty has a limited effect on survival among those with poor PS. These findings suggest that PS, not frailty, drives survival on intensive treatment.

Efficacy and Safety of Allopurinol and Febuxostat in Patients With Gout and CKD: Subgroup Analysis of the STOP Gout Trial.

RATIONALE & OBJECTIVE: We conducted a prespecified examination of the efficacy and safety of allopurinol and febuxostat administered using a treat-to-target strategy in trial participants with chronic kidney disease (CKD). STUDY DESIGN: Prespecified sub cohort analysis of a randomized controlled trial. SETTING: & Participants: A sub study of the STOP Gout trial in participants with CKD. CKD was defined as an eGFR 30-59 mL/min/1.73 m2 at baseline. EXPOSURE: Trial participants with CKD and gout and serum urate (sUA) concentration ≥6.8 mg/dL were randomized 1:1 to receive allopurinol or febuxostat. Urate lowering therapy (ULT) was titrated during weeks 0-24 to achieve a goal sUA of <6.0 mg/dl (<5.0 mg/dl with tophi) (Phase 1) and maintained during weeks 25-48 (Phase 2). Gout flare was assessed between weeks 49-72 (Phase 3). OUTCOME: Gout flare between weeks 49-72 (Phase 3) was the primary outcome. Secondary outcomes included sUA goal achievement and ULT dosing at end of Phase 2, and serious adverse events (SAEs). ANALYTICAL APPROACH: Outcomes between treatment groups were compared using logistic regression models for binary outcomes, and Poisson regression for flare rates. Multivariable models were subsequently used, adjusting for factors identified to be imbalanced by treatment arm. RESULTS: 351 of 940 participants (37.3%) had CKD; 277 were assessed for the primary outcome. Fewer patients randomized to allopurinol had a flare during phase 3 (32% vs 45%; p=0.02) despite similar attainment of sUA goal (79% vs. 81%; p=0.6) by the end of Phase 2. Acute kidney injury (AKI) was more common in participants with stage 3 CKD randomized to allopurinol compared to febuxostat. LIMITATIONS: Limited power to assess infrequent safety events, largely male, older population. CONCLUSIONS: Allopurinol and febuxostat are similarly efficacious and well-tolerated in the treatment of gout in people with CKD when used in a treat-to-target regimen.

Venous thromboembolism risk in cancer patients receiving first-line immune checkpoint inhibitor versus chemotherapy.

It remains unclear if immune checkpoint inhibitor (ICI) therapy is associated with higher rate of venous thromboembolism (VTE) compared with cytotoxic chemotherapy (chemo) in patients with comparable cancer type, staging, and comorbidities. Using the national Veterans Affairs healthcare system database from 2016 to 2021, we performed a propensity score (PS)-weighted retrospective cohort study to compare the incidence of VTE in patients with selected stage III/IV cancer receiving first-line ICI versus chemo. The PS model utilized overlap weights to balance age, sex, race, treatment year, VTE history, paralysis/immobilization, prolonged hospitalization, cancer type, staging, time between diagnosis and treatment, and National Cancer Institute comorbidity index. Weighted Cox regressions with robust standard error were used to assess the hazard ratio (HR) and 95% confidence interval (CI). We found that among comparable advanced cancers, first-line ICI (n = 1823) and first-line chemo (n = 6345) had similar rates of VTE (8.49% for ICI and 8.36% for chemo at 6 months). The weighted HR was 1.06 (95% CI 0.88-1.26) for ICI versus chemo. In a subgroup analysis restricted to lung cancers, first-line ICI/chemo (n = 828), ICI monotherapy (n = 428), and chemo monotherapy (n = 4371) had similar rates of VTE (9.60% for ICI/chemo, 10.04% for ICI, and 8.91% for chemo at 6 months). The weighted HR was 1.05 (95% CI 0.77-1.42) for ICI versus chemo, and 1.08 (95% CI 0.83-1.42) for ICI/chemo versus chemo. In conclusion, ICI as a systemic therapy has a similarly elevated risk as cytotoxic chemo for VTE occurrence in cancer patients. This finding can inform future prospective studies exploring thromboprophylaxis strategies.

Validation of algorithms to select patients with multiple myeloma and patients initiating myeloma treatment in the national Veterans Affairs Healthcare System.

BACKGROUND: We aimed to evaluate and compare the performance of multiple myeloma (MM) selection algorithms for use in Veterans Affairs (VA) research. METHODS: Using the VA Corporate Data Warehouse (CDW), the VA Cancer Registry (VACR), and VA pharmacy data, we randomly selected 500 patients from 01/01/1999 to 06/01/2021 who had (1) either one MM diagnostic code OR were listed in the VACR as having MM AND (2) at least one MM treatment code. A team reviewed oncology notes for each veteran to annotate details regarding MM diagnosis and initial treatment within VA. We evaluated inter-annotator agreement and compared the performance of four published algorithms (two developed and validated external to VA data and two used in VA data). RESULTS: A total of 859 patients were reviewed to obtain 500 patients who were annotated as having MM and initiating MM treatment in VA. Agreement was high among annotators for all variables: MM diagnosis (98.3% agreement, Kappa = 0.93); initial treatment in VA (91.8% agreement; Kappa = 0.77); and initial treatment classification (87.6% agreement; Kappa = 0.86). VA Algorithms were more specific and had higher PPVs than non-VA algorithms for both MM diagnosis and initial treatment in VA. We developed the "VA Recommended Algorithm," which had the highest PPV among all algorithms in identifying patients diagnosed with MM (PPV = 0.98, 95% CI = 0.95-0.99) and in identifying patients who initiated their MM treatment in VA (PPV = 0.93, 95% CI = 0.90-0.96). CONCLUSION: Our VA Recommended Algorithm optimizes sensitivity and PPV for cohort selection and treatment classification.

Practical issues in pragmatic trials: the implementation of the Diuretic Comparison Project.

BACKGROUND/AIMS: The US Department of Veterans Affairs Point of Care Clinical Trial Program conducts studies that utilize informatics infrastructure to integrate clinical trial protocols into routine care delivery. The Diuretic Comparison Project compared hydrochlorothiazide to chlorthalidone in reduction of major cardiovascular events in subjects with hypertension. Here we describe the cultural, technical, regulatory, and logistical challenges and solutions that enabled successful implementation of this large pragmatic comparative effectiveness Point of Care clinical trial. METHODS: Patients were recruited from 72 Veterans Affairs Healthcare Systems using centralized processes for subject identification, obtaining informed consent, data collection, safety monitoring, site communication, and endpoint identification with minimal perturbation of the local clinical care ecosystem. Patients continued to be managed exclusively by their clinical care providers without protocol specified study visits, treatment recommendations, or data collection extraneous to routine care. Centralized study processes were operationalized through the application layer of the electronic health record via a data coordinating center staffed by clinical nurses, data scientists, and statisticians without site-based research coordinators. Study data was collected from the Veterans Affairs electronic health record supplemented by Medicare and National Death Index data. RESULTS: The study exceeded its enrolled goal (13,523 subjects) and followed subjects for the 5-year study duration. The key determinant of program success was collaboration between researchers, regulators, clinicians, and administrative staff at the site level to customize study procedures to align with local clinical practice. This flexibility was enabled by designation of the study as minimal risk and determination that clinical care providers were not engaged in research by the Veterans Affairs Central Institutional Review Board. Cultural, regulatory, technical, and logistical problems were identified and solved through iterative collaboration between clinical and research entities. Paramount among these problems was customization of the Veterans Affairs electronic health record and data systems to accommodate study procedures. CONCLUSIONS: Leveraging clinical care for large-scale clinical trials is feasible but requires a rethinking of traditional clinical trial design (and regulation) to better meet requirements of clinical care ecosystems. Study designs must accommodate site-specific practice variation to reduce the impact on clinical care. A tradeoff thus exists between designing trial processes tailored to expedite local study implementation versus those to produce a more refined response to the research question. The availability of a uniform and flexible electronic health record in the Department of Veterans Affairs played a major role in the success of the trial. Conducting Point of Care research in other healthcare systems without such research-friendly infrastructure presents a more formidable challenge.

Risk factors of SARS-CoV-2 infection and complications from COVID-19 in lung cancer patients.

BACKGROUND: Identifying lung cancer patients at an increased risk of getting SARS-CoV-2-related complications will facilitate tailored therapy to maximize the benefit of anti-cancer therapy, while decreasing the likelihood of COVID-19 complications. This analysis aimed to identify the characteristics of lung cancer patients that predict for increased risk of death or serious SARS-CoV-2 infection. PATIENTS AND METHODS: This was a retrospective cohort study of patients with lung cancer diagnosed October 1, 2015, and December 1, 2020, and a diagnosis of COVID-19 between February 2, 2020, and December 1, 2020, within the Veterans Health Administration. Serious SARS-CoV-2 infection was defined as hospitalization, ICU admission, or mechanical ventilation or intubation within 2 weeks of COVID-19 diagnosis. For categorical variables, differences were assessed using Χ2 tests, while Kruskal-Wallis rank-sum test was used for continuous variables. Multivariable logistic regression models were fit relative to onset of serious SARS-CoV-2 infection and death from SARS-CoV-2 infection. RESULTS: COVID-19 infection was diagnosed in 352 lung cancer patients. Of these, 61 patients (17.3%) died within four weeks of diagnosis with COVID-19, and 42 others (11.9%) experienced a severe infection. Patients who had fatal or severe infection were older and had lower hemoglobin levels than those with mild or moderate infection. Factors associated with death from SARS-CoV-2 infection included increasing age, immune checkpoint inhibitor therapy and low hemoglobin level. CONCLUSIONS:  The mortality of lung cancer patients from COVID-19 disease in the present cohort was less than previously reported in the literature. The identification of risk factors associated with severe or fatal outcomes informs management of patients with lung cancer who develop COVID-19 disease.

The Gulf War Era Cohort and Biorepository: A Longitudinal Research Resource of Veterans of the 1990-1991 Gulf War Era.

The US Department of Veterans Affairs (VA) Gulf War Era Cohort and Biorepository (GWECB) is a nationally representative longitudinal cohort of US veterans who served during the 1990-1991 Gulf War era. The GWECB combines survey data, such as demographic, health behavior, and environmental exposure data; medical records; and a linked biorepository of blood specimens that can support a broad range of future research regarding health concerns unique to veterans of this era. To build this resource, the VA Cooperative Studies Program initiated a pilot study (2014-2016) to establish the GWECB and evaluate the processes required to build and maintain the resource. Participants (n = 1,275) consented to future sharing of their data and biospecimens for research purposes. Here we describe the pilot study, including recruitment and enrollment procedures, data collection and management, quality control, and challenges experienced. The GWECB data available to investigators under approved sharing mechanisms and the procedures for accessing them are extensively detailed. The study's consenting documents and a website link for the research survey are provided. Our hope is that new research drawing on the GWECB data and biospecimens will result in effective treatments and improved approaches to address the health concerns of Gulf War-era veterans.

Rheumatoid arthritis triple therapy compared with etanercept: difference in infectious and gastrointestinal adverse events.

Objective: The main aim of this study was to examine the differences between triple therapy (T: SSZ and HCQ added to MTX) and etanercept (E) added to MTX with regard to the infectious and gastrointestinal (GI) adverse events (AEs) reported in The Rheumatoid Arthritis Comparison of Active Therapies Trial. Methods: The patients were 353 RA MTX incomplete responders who were randomized to T (n = 178) or E (n = 175). Of these, 88 patients were switched to the alternative treatment from the initial treatment (E or T) at 24 weeks per protocol. Infectious and GI serious AEs (SAEs) and non-serious AEs (NAEs) were reported during 48 and 4 weeks after the intervention period. Generalized linear models were used to estimate the incidence rate ratios (IRRs) of AEs between the two therapies. Results: Patients on E therapy were more likely to have infectious NAEs (IRR = 1.56, 95% CI: 1.11, 2.19). There was a greater number of infectious SAEs that occurred when patients received E than T therapy [12 E (6.9%) vs 4 T (2.2%), P = 0.19]. Pneumonia was the most common infectious SAE for both treatments [6 E (3.4%) and 2 T (1.1%)]. Conversely, patients who were on E were less likely to have GI NAEs than those on T therapy (IRR = 0.62, 95% CI: 0.40, 0.94). The most common GI SAE reported was GI haemorrhage, which occurred among three patients on E (1.7%). Conclusion: This study provides evidence of different likelihoods of infectious and GI AEs associated with two common, equally effective treatments for RA patients who have had incomplete responses to MTX. Trial registration: ClinicalTrials.gov, http://clinicaltrials.gov , NCT00405275.

Racial and Ethnic Disparity for Cancer Mortality in General and Single-Payer Healthcare Systems in the United States.

BACKGROUND: It remains unclear what factors significantly drive racial disparity in cancer survival in the United States (US). We compared adjusted mortality outcomes in cancer patients from different racial and ethnic groups on a population level in the US and a single-payer healthcare system. PATIENTS AND METHODS: We selected adult patients with incident solid and hematologic malignancies from the Surveillance, Epidemiology, and End Results (SEER) 2011-2020 and Veteran Affairs national healthcare system (VA) 2011-2021. We classified the self-reported NIH race and ethnicity into non-Hispanic White (NHW), non-Hispanic Black (NHB), non-Hispanic Asian Pacific Islander (API), and Hispanic. Cox regression models for hazard ratio of racial and ethnic groups were built after adjusting confounders in each cohort. RESULTS: The study included 3,104,657 patients from SEER and 287,619 patients from VA. There were notable differences in baseline characteristics in the two cohorts. In SEER, adjusted HR for mortality was 1.12 (95% CI, 1.12-1.13), 1.03 (95% CI, 1.03-1.04), and 0.91 (95% CI, 0.90-0.92), for NHB, Hispanic, and API patients, respectively, vs. NHW. In VA, adjusted HR was 0.94 (95% CI, 0.92-0.95), 0.84 (95% CI, 0.82-0.87), and 0.96 (95% CI, 0.93-1.00) for NHB, Hispanic, and API, respectively, vs. NHW. Additional subgroup analyses by cancer types, age, and sex did not significantly change these associations. CONCLUSIONS: Racial disparity continues to persist on a population level in the US especially for NHB vs. NHW patients, where the adjusted mortality was 12% higher in the general population but 6% lower in the single-payer VA system.

Determinants of Achieving Serum Urate Goal with Treat-to-Target Urate-Lowering Therapy in Gout.

OBJECTIVE: Using trial data comparing treat-to-target allopurinol and febuxostat in gout, we examined participant characteristics associated with serum urate (SU) goal achievement. METHODS: Participants with gout and SU ≥6.8 mg/dL were randomized to allopurinol or febuxostat, titrated during weeks 0 to 24, and maintained weeks 25 to 48. Participants were considered to achieve SU goal if the mean SU from weeks 36, 42, and 48 was <6.0 mg/dL or <5 mg/dL if tophi were present. Possible determinants of treatment response were preselected and included sociodemographics, comorbidities, diuretic use, health-related quality of life (HRQoL), body mass index, and gout measures. Determinants of SU response were assessed using multivariable logistic regression with additional analyses to account for treatment adherence. RESULTS: Of 764 study participants completing week 48, 618 (81%) achieved SU goal. After multivariable adjustment, factors associated with a greater likelihood of SU goal achievement included older age (adjusted odds ratio [aOR] 1.40 per 10 years), higher education (aOR 2.02), and better HRQoL (aOR 1.17 per 0.1 unit). Factors associated with a lower odds of SU goal achievement included non-White race (aORs 0.32-0.47), higher baseline SU (aOR 0.83 per 1 mg/dL), presence of tophi (aOR 0.29), and the use of diuretics (aOR 0.52). Comorbidities including chronic kidney disease, hypertension, diabetes, and cardiovascular disease were not associated with SU goal achievement. Results were not meaningfully changed in analyses accounting for adherence. CONCLUSIONS: Several patient-level factors were predictive of SU goal achievement among patients with gout who received treat-to-target urate-lowering therapy (ULT). Approaches that accurately predict individual responses to treat-to-target ULT hold promise in facilitating personalized management and improving outcomes in patients with gout.

Transfer Learning for Mortality Prediction in Non-Small Cell Lung Cancer with Low-Resolution Histopathology Slide Snapshots.

High-resolution whole slide image scans of histopathology slides have been widely used in recent years for prediction in cancer. However, in some cases, clinical informatics practitioners may only have access to low-resolution snapshots of histopathology slides, not high-resolution scans. We evaluated strategies for training neural network prognostic models in non-small cell lung cancer (NSCLC) based on low-resolution snapshots, using data from the Veterans Affairs Precision Oncology Data Repository. We compared strategies without transfer learning, with transfer learning from general domain images, and with transfer learning from publicly available high-resolution histopathology scans. We found transfer learning from high-resolution scans achieved significantly better performance than other strategies. Our contribution provides a foundation for future development of prognostic models in NSCLC that incorporate data from low-resolution pathology slide snapshots alongside known clinical predictors.

Building Research Infrastructure to Develop Greater Learning Efficiencies (BRIDGE).

In this manuscript, we outline our developed version of a Learning Health System (LHS) in oncology implemented at the Department of Veterans Affairs (VA). Transferring healthcare into an LHS framework has been one of the spearpoints of VA's Central Office and given the general lack of evidence generated through randomized control clinical trials to guide medical decisions in oncology, this domain is one of the most suitable for this change. We describe our technical solution, which includes a large real-world data repository, a data science and algorithm development framework, and the mechanism by which results are brought back to the clinic and to the patient. Additionally, we propose the need for a bridging framework that requires collaboration between informatics specialists and medical professionals to integrate knowledge generation into the clinical workflow at the point of care.

Phenotyping Hepatic Immune-Related Adverse Events in the Setting of Immune Checkpoint Inhibitor Therapy.

PURPOSE: We present and validate a rule-based algorithm for the detection of moderate to severe liver-related immune-related adverse events (irAEs) in a real-world patient cohort. The algorithm can be applied to studies of irAEs in large data sets. METHODS: We developed a set of criteria to define hepatic irAEs. The criteria include: the temporality of elevated laboratory measurements in the first 2-14 weeks of immune checkpoint inhibitor (ICI) treatment, steroid intervention within 2 weeks of the onset of elevated laboratory measurements, and intervention with a duration of at least 2 weeks. These criteria are based on the kinetics of patients who experienced moderate to severe hepatotoxicity (Common Terminology Criteria for Adverse Events grades 2-4). We applied these criteria to a retrospective cohort of 682 patients diagnosed with hepatocellular carcinoma and treated with ICI. All patients were required to have baseline laboratory measurements before and after the initiation of ICI. RESULTS: A set of 63 equally sampled patients were reviewed by two blinded, clinical adjudicators. Disagreements were reviewed and consensus was taken to be the ground truth. Of these, 25 patients with irAEs were identified, 16 were determined to be hepatic irAEs, 36 patients were nonadverse events, and two patients were of indeterminant status. Reviewers agreed in 44 of 63 patients, including 19 patients with irAEs (0.70 concordance, Fleiss' kappa: 0.43). By comparison, the algorithm achieved a sensitivity and specificity of identifying hepatic irAEs of 0.63 and 0.81, respectively, with a test efficiency (percent correctly classified) of 0.78 and outcome-weighted F1 score of 0.74. CONCLUSION: The algorithm achieves greater concordance with the ground truth than either individual clinical adjudicator for the detection of irAEs.

Comparison of Gout Flares With the Initiation of Treat-to-Target Allopurinol and Febuxostat: A Post-Hoc Analysis of a Randomized Multicenter Trial.

OBJECTIVE: Initiating urate-lowering therapy (ULT) in gout can precipitate arthritis flares. There have been limited comparisons of flare risk during the initiation and escalation of allopurinol and febuxostat, administered as a treat-to-target strategy with optimal anti-inflammatory prophylaxis. METHODS: This was a post-hoc analysis of a 72-week randomized, double-blind, placebo-controlled, noninferiority trial comparing the efficacy of allopurinol and febuxostat. For this analysis, the occurrence of flares was examined during weeks 0 to 24 when ULT was initiated and titrated to a serum urate (sUA) goal of less than 6 mg/dl (<5 mg/dl if tophi). Flares were assessed at regular intervals through structured participant interviews. Predictors of flare, including treatment assignment, were examined using multivariable Cox proportional hazards regression. RESULTS: Study participants (n = 940) were predominantly male (98.4%) and had a mean age of 62.1 years with approximately equal proportions receiving allopurinol or febuxostat. Mean baseline sUA was 8.5 mg/dl and all participants received anti-inflammatory prophylaxis (90% colchicine). In a multivariable model, there were no significant associations of ULT treatment (hazard ratio [HR] 1.17; febuxostat vs allopurinol), ULT-dose escalation (HR 1.18 vs no escalation), prophylaxis type, or individual comorbidity with flare and no evidence of ULT-dose escalation interaction. Factors independently associated with flare risk during ULT initiation/escalation included younger age, higher baseline sUA, and absence of tophi. CONCLUSION: These results demonstrate that gout flare risk during the initiation and titration of allopurinol is similar to febuxostat when these agents are administered according to a treat-to-target strategy using gradual ULT-dose titration and best practice gout flare prophylaxis.

Brain tumors in United States military veterans.

BACKGROUND: Comprehensive analysis of brain tumor incidence and survival in the Veteran population has been lacking. METHODS: Veteran data were obtained from the Veterans Health Administration (VHA) Medical Centers via VHA Corporate Data Warehouse. Brain tumor statistics on the overall US population were generated from the Central Brain Tumor Registry of the US data. Cases were individuals (≥18 years) with a primary brain tumor, diagnosed between 2004 and 2018. The average annual age-adjusted incidence rates (AAIR) and 95% confidence intervals were estimated per 100 000 population and Kaplan-Meier survival curves evaluated overall survival outcomes among Veterans. RESULTS: The Veteran population was primarily white (78%), male (93%), and between 60 and 64 years old (18%). Individuals with a primary brain tumor in the general US population were mainly female (59%) and between 18 and 49 years old (28%). The overall AAIR of primary brain tumors from 2004 to 2018 within the Veterans Affairs cancer registry was 11.6. Nonmalignant tumors were more common than malignant tumors (AAIR:7.19 vs 4.42). The most diagnosed tumors in Veterans were nonmalignant pituitary tumors (AAIR:2.96), nonmalignant meningioma (AAIR:2.62), and glioblastoma (AAIR:1.96). In the Veteran population, survival outcomes became worse with age and were lowest among individuals diagnosed with glioblastoma. CONCLUSIONS: Differences between Veteran and US populations can be broadly attributed to demographic composition differences of these groups. Prior to this, there have been no reports on national-level incidence rates and survival outcomes for Veterans. These data provide vital information that can drive efforts to understand disease burden and improve outcomes for individuals with primary brain tumors.

Matching Patients to Accelerate Clinical Trials (MPACT): Enabling Technology for Oncology Clinical Trial Workflow.

Clinical trial enrollment is impeded by the significant time burden placed on research coordinators screening eligible patients. With 50,000 new cancer cases every year, the Veterans Health Administration (VHA) has made increased access for Veterans to high-quality clinical trials a priority. To aid in this effort, we worked with research coordinators to build the MPACT (Matching Patients to Accelerate Clinical Trials) platform with a goal of improving efficiency in the screening process. MPACT supports both a trial prescreening workflow and a screening workflow, employing Natural Language Processing and Data Science methods to produce reliable phenotypes of trial eligibility criteria. MPACT also has a functionality to track a patient's eligibility status over time. Qualitative feedback has been promising with users reporting a reduction in time spent on identifying eligible patients.

Baseline correlates of frailty and its association with survival in United States veterans with acute myeloid leukemia.

Frailty is an important construct to measure in acute myeloid leukemia (AML). We used the Veterans Affairs Frailty Index (VA-FI) - calculated using readily available data within the VA's electronic health records - to measure frailty in U.S. veterans with AML. Of the 1166 newly diagnosed and treated veterans with AML between 2012 and 2022, 722 (62%) veterans with AML were classified as frail (VA-FI > 0.2). At a median follow-up of 252.5 days, moderate-severely frail veterans had significantly worse survival than mildly frail, and non-frail veterans (median survival 179 vs. 306 vs. 417 days, p < .001). Increasing VA-FI severity was associated with higher mortality. A model with VA-FI in addition to the European LeukemiaNet (ELN) risk classification and other covariates statistically outperformed a model containing the ELN risk and other covariates alone (p < .001). These findings support the VA-FI as a tool to expand frailty measurement in research and clinical practice for informing prognosis in veterans with AML.

Trends in Fracture Rates Over Two Decades Among Veterans With Ankylosing Spondylitis.

OBJECTIVE: There is an increased risk of fracture in individuals with ankylosing spondylitis (AS) compared to the general population, possibly due to systemic inflammatory effects. The use of tumor necrosis factor inhibitors (TNFi) may reduce fracture risk by inhibiting inflammation. We assessed fracture rates in AS versus non-AS comparators and whether these rates have changed since the introduction of TNFi. METHODS: We used the national Veterans Affairs database to identify adults ≥18 years old with ≥1 International Classification of Diseases, Ninth Revision (ICD-9)/ICD-10 code for AS and at least 1 disease-modifying antirheumatic drug prescription. As comparators, we selected a random sample of adults without AS diagnosis codes. We calculated fracture incidence rates for AS and comparators, with direct standardization to the cohort structure in 2017. To compare fracture rates from 2000 to 2002 (pre-TNFi) versus 2004-2020 (TNFi era), we performed an interrupted time series analysis. RESULTS: We included 3,794 individuals with AS (mean age 53 years, 92% male) and 1,152,805 comparators (mean age 60 years, 89% male). For AS, the incidence rate of fractures increased from 7.9/1,000 person-years in 2000 to 21.6/1,000 person-years in 2020. The rate also increased among comparators, although the ratio of fracture rates (AS/comparators) remained relatively stable. In the interrupted time series, the fracture rate for AS patients in the TNFi era was nonsignificantly increased compared to the pre-TNFi era. CONCLUSION: Fracture rates have increased over time for both AS and non-AS comparators. The fracture rate in individuals with AS did not decrease after TNFi introduction in 2003.