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In the United States, significant racial and ethnic disparities exist in chronic kidney disease (CKD) and its management. Hemodialysis constitutes the main stay of renal replacement therapy for end-stage kidney disease (ESKD), which is initiated using central venous catheters (CVC) in most CKD patients in the United States. Black ESKD patients have higher usage and greater time on CVC for hemodialysis compared to White patients. This trend places Black patients at a potentially higher risk for CVC-related complications such as central venous stenosis (CVS). We posited that Black patients would have a higher prevalence and a greater risk of CVS. A retrospective review was performed of ESKD patients who underwent a fistulogram for dialysis access malfunction. CVS was defined as > 50% stenosis in the central veins. Fistulograms of 428 ESKD patients were adjudicated, and CVS was noted in 167 of these patients. Of the entire cohort, 370 fistulograms belonged to self-reported unique Black and White ESKD patients, of whom 137 patients were noted to have CVS. There was no difference in the of CVS between Black (40%) and White (41%) ESKD patients. However, a higher severity of stenosis (>70%) (P = 0.03) was noted in White ESKD patients. An unadjusted model showed a significant association between CVS and cardiovascular disease and the use of CVCs. The risk-adjusted model showed a significant association between diabetes and CVS. Unlike arterial stenotic lesions, this work for the first time demonstrated higher prevalence of severe venous stenotic lesions in White ESKD patients and linked diabetes to stenotic venous disease. This work paves the way for future studies investigating the risk and influence of race and ethnicity on CVS using a larger and diverse data set.

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., (© 2023 Wiley Periodicals LLC.)

Introduction: PD-L1 expression is used to determine oncology patients' response to and eligibility for immunologic treatments; however, PD-L1 expression status often only exists in unstructured clinical notes, limiting ability to use it in population-level studies. Methods: We developed and evaluated a machine learning based natural language processing (NLP) tool to extract PD-L1 expression values from the nationwide Veterans Affairs electronic health record system. Results: The model demonstrated strong evaluation performance across multiple levels of label granularity. Mean precision of the overall PD-L1 positive label was 0.859 (sd, 0.039), recall 0.994 (sd, 0.013), and F1 0.921 (0.024). When a numeric PD-L1 value was identified, the mean absolute error of the value was 0.537 on a scale of 0 to 100. Conclusion: We presented an accurate NLP method for deriving PD-L1 status from clinical notes. By reducing the time and manual effort needed to review medical records, our work will enable future population-level studies in cancer immunotherapy.

Venous thromboembolism (VTE) is a significant complication for cancer patients undergoing systemic therapy. We performed an independent external validation for a recently derived and validated a novel electronic health record (EHR) VTE risk score in a comprehensive cancer center. Adult patients with incident cancer diagnoses were identified from MD Anderson Cancer Center Tumor Registry 1/2017-1/2021. Baseline covariates extracted at the time of first-line systemic therapy included demographics, cancer site/histology, stage, treatment, complete blood count, body mass index, recent prolonged hospitalization, and history of VTE or paralysis. VTE was ascertained using an institution-specific natural language processing radiology algorithm (positive predictive value of 94.8%). The median follow-up for 21 142 cancer patients was 8.1 months. There were 1067 (5.7%) VTE within 6 months after systemic therapy. The distribution of the novel score for 0-, 1, 2, 3, 4, 5+ was 5661, 3558, 3462, 3489, 2918, and 2054; while the corresponding 6-month VTE incidence was 1.3%, 3.1%, 5.4%, 7.3%, 9.3%, and 13.8%, respectively (c statistic 0.71 [95% CI 0.69-0.72] with excellent calibration). In comparison, the Khorana score had a c statistic of 0.64 [95% CI 0.62-0.65]. The two risk scores had 80% concordance; the novel score reclassified 20% of Khorana score (3530 low-to-high with 9.0% VTE; 734 high-to-low with 3.4% VTE) and led to a 25% increment in VTEs captured in the high-risk group. In conclusion, the novel score demonstrated consistent discrimination and calibration across cohorts with heterogenous demographics. It could become a new standard to select high-risk populations for clinical trials and VTE monitoring., (© 2023 Wiley Periodicals LLC.)

Purpose: Venous thromboembolism (VTE), especially pulmonary embolism (PE) and lower extremity deep vein thrombosis (LE-DVT), is a serious and potentially preventable complication for patients with cancer undergoing systemic therapy., Methods: Using retrospective data from patients diagnosed with incident cancer from 2011-2020, we derived a parsimonious risk assessment model (RAM) using least absolute shrinkage and selection operator regression from the Harris Health System (HHS, n = 9,769) and externally validated it using the Veterans Affairs (VA) health care system (n = 79,517). Bootstrapped c statistics and calibration curves were used to assess external model discrimination and fit. Dichotomized risk strata using integer scores were created and compared against the Khorana score (KS)., Results: Incident VTE and PE/LE-DVT at 6 months occurred in 590 (6.2%) and 437 (4.6%) patients in HHS and 4,027 (5.1%) and 3,331 (4.2%) patients in the VA health care system. Assessed at the time of systemic therapy initiation, the new RAM included components of the KS with the modified cancer subtype, cancer staging, systemic therapy class, history of VTE, history of paralysis/immobility, recent hospitalization, and Asian/Pacific Islander race. The c statistic was 0.71 in HHS and 0.68 in the VA health care system (compared with 0.65 and 0.60, respectively, for KS). Furthermore, the new RAM appropriately reclassified 28% of patients and increased the proportion of VTEs in the high-risk group from 37% to 68% in the validation data set., Conclusion: The novel RAM stratified patients with cancer into a high-risk group with 8%-10% cumulative incidence of VTE and 7% PE/LE-DVT at 6 months ( v 3% and 2%, respectively, in the low-risk group). The model had improved performance over the original KS and doubled the number of VTE events in the high-risk stratum. We encourage additional external validation from prospective studies.[Media: see text].

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer., (© 2023. The Author(s).)

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., (© 2022 John Wiley & Sons Ltd. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

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 Χ 2 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., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: Cardiovascular disease (CVD) is the leading cause of death in men with prostate cancer (PC). Accumulated stress plays an important role in CVD development. The cumulative burden of chronic stress and life events can be measured using allostatic load (AL)., Methods: The initial cohort included males aged 18 years and older diagnosed with PC (2005-2019). AL was modeled as an ordinal variable (0-11). Fine-Gray competing risk regressions measured the impact of precancer diagnosis AL and postdiagnosis AL in 2-year major cardiac events (MACE). The effect of AL changes over time on MACE development was calculated via piecewise Cox regression (before, and 2 months, 6 months, and 1 year after PC diagnosis)., Results: We included 5261 PC patients of which 6.6% had a 2-year MACE. For every 1-point increase in AL before and within 60 days after PC diagnosis, the risk of MACE increased 25% (adjusted hazard ratio [aHR] =1.25, 95% confidence interval [CI] = 1.18 to 1.33) and 27% (aHR = 1.27, 95% CI = 1.20 to 1.35), respectively. Using AL as a time-varying exposure, the risk of MACE increased 19% (aHR = 1.19, 95% CI = 1.11 to 1.27), 22% (aHR = 1.22, 95% CI = 1.14 to 1.33), 28% (aHR = 1.28, 95% CI = 1.23 to 1.33), and 31% (aHR = 1.31, 95% CI = 1.27 to 1.35) for every 1-point increase in AL before, 2 months after, 6 months after, and 1 year after PC diagnosis, respectively., Conclusion: AL and its changes over time are associated with MACE in PC patients, suggesting a role of a biological measure of stress as a marker of CVD risk among men with PC., (© The Author(s) 2023. Published by Oxford University Press.)

Background: The global COVID-19 pandemic is an opportunity to evaluate factors associated with high levels of adoption of different therapeutics in a real-world setting. The aim of this nationwide, retrospective cohort study was to evaluate the diffusion and adoption of novel therapeutics with an emerging evidence basis and to identify factors that influenced physicians' treatment decisions., Methods: Cohort creation: A cohort of Veteran patients with a microbiologically confirmed diagnosis of SARS-CoV2 were identified, and cases were classified by disease severity (outpatient, inpatient with mild and severe disease, intensive care unit ICU]). After classification of disease severity, the proportion of cases (outpatients) and admissions (inpatients) in each category receiving each type of medication were plotted as a function of time. Identification of milestones and guidance changes: Key medications used for the management of COVID-19 milestones in the release of primary research results in various forms (e.g. via press release, preprint or publication in a traditional medical journal), policy events and dates of key guidelines were identified and plotted as a timeline. After a timeline was created, time points were compared to changes in medication use, and factors potentially impacting the magnitude (i.e. proportion of patients who received the treatment) and the speed (i.e. the slope of the change in use) of practice changes were evaluated., Results: Dexamethasone and remdesivir, the first two medications with clinical trial data to support their use, underwent the most rapid, complete and sustained diffusion and adoption; the majority of practice changes occurred after press releases and preprints were available and prior to guideline changes, although some additional uptake occurred following guideline updates. Medications that were not "first in class", that were identified later in the pandemic, and that had higher perceived risk had slower and less complete uptake regardless of the strength and quality of the evidence supporting the intervention., Conclusions: Our findings suggest that traditional and social media platforms and preprint releases were major catalysts of practice change, particularly prior to the identification of effective treatments. The "first available treatment in class" impact appeared to be the single most important factor determining the speed and scope of diffusion., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: The Surveillance, Epidemiology, and End Results (SEER) program reflects a third of the population of the United States. However, SEER may not be generalizable to the veteran population. Because veterans comprise a high-risk population, this discrepancy may limit our understanding of the epidemiology of melanoma in such high-risk populations., Objectives: To assess differences in demographics, tumor characteristics, and melanoma-specific survival (MSS) in veterans compared to the general population., Methods: Data were collected from the Veterans Affairs Cancer Registry (VACR) and SEER (18 registries) from 2009 to 2017., Results: We identified 15,334 veterans and 166,265 SEER patients with melanoma. Veterans were more likely to present with regional or distant disease (17.5% vs 13.0% in SEER). In VACR relative to SEER, the 5-year MSS was lower across all ages, except those diagnosed at ≥80 years. From 2009 to 2017, MSS by stage was lower across all stages in VACR. However, for stage IV melanomas diagnosed in 2015 to 2017 compared to 2011-2014, 2-year MSS increased from 37.8% to 51.5% in VACR versus 36.4% to 44.8% in SEER., Limitations: Unique veteran demographics and missing data inherent to VACR., Conclusion: Compared to SEER, veterans with melanoma were diagnosed at later stages; however, both exhibited recent improvement in stage IV MSS., Competing Interests: Conflicts of interest None., (Published by Elsevier Inc.)

Introduction: Tumor necrosis factor (TNF) inhibitors are widely used to treat rheumatoid arthritis (RA) and their potential to retard Alzheimer's disease (AD) progression has been reported. However, their long-term effects on the dementia/AD risk remain unknown., Methods: A propensity scored matched retrospective cohort study was conducted among 40,207 patients with RA within the US Veterans Affairs health-care system from 2000 to 2020., Results: A total of 2510 patients with RA prescribed TNF inhibitors were 1:2 matched to control patients. TNF inhibitor use was associated with reduced dementia risk (hazard ratio [HR]: 0.64, 95% confidence interval [CI]: 0.52-0.80), which was consistent as the study period increased from 5 to 20 years after RA diagnosis. TNF inhibitor use also showed a long-term effect in reducing the risk of AD (HR: 0.57, 95% CI: 0.39-0.83) during the 20 years of follow-up., Conclusion: TNF inhibitor use is associated with lower long-term risk of dementia/AD among US veterans with RA., (© 2021 the Alzheimer's Association.)

Background Vascular function is compromised in Alzheimer disease (AD) years before amyloid and tau pathology are detected and a substantial body of work shows abnormal platelet activation states in patients with AD. The aim of our study was to investigate whether platelet function in middle age is independently associated with future risk of AD. Methods and Results We examined associations of baseline platelet function with incident dementia risk in the community-based FHS (Framingham Heart Study) longitudinal cohorts. The association between platelet function and risk of dementia was evaluated using the cumulative incidence function and inverse probability weighted Cox proportional cause-specific hazards regression models, with adjustment for demographic and clinical covariates. Platelet aggregation response was measured by light transmission aggregometry. The final study sample included 1847 FHS participants (average age, 53.0 years; 57.5% women). During follow-up (median, 20.5 years), we observed 154 cases of incident dementia, of which 121 were AD cases. Results from weighted models indicated that platelet aggregation response to adenosine diphosphate 1.0 µmol/L was independently and positively associated with dementia risk, and it was preceded in importance only by age and hypertension. Sensitivity analyses showed associations with the same directionality for participants defined as adenosine diphosphate hyper-responders, as well as the platelet response to 0.1 µmol/L epinephrine. Conclusions Our study shows individuals free of antiplatelet therapy with a higher platelet response are at higher risk of dementia in late life during a 20-year follow-up, reinforcing the role of platelet function in AD risk. This suggests that platelet phenotypes may be associated with the rate of dementia and potentially have prognostic value.

Background: Disparities based on socioeconomic factors such as race, ethnicity, marital status, and insurance status are associated with pancreatic cancer resection, but these disparities are usually not observed for survival after resection. It is unknown if there are disparities when patients undergo their treatment in a non-fee-for-service, equal-access healthcare system such as the Veterans Health Administration (VHA)., Methods: Patients having T1-T3 M0 pancreatic adenocarcinoma diagnosed between 2006 and 2017 were identified from the VHA Corporate Data Warehouse. Socioeconomic, demographic, and tumor variables associated with resection and survival were assessed., Results: In total, 2580 patients with early-stage pancreatic cancer were identified. The resection rate was 36.5%. Surgical resection was independently associated with younger age [odds ratio (OR) 0.94, p < 0.001], White race (OR 1.35, p = 0.028), married status (OR 1.85, p = 0.001), and employment status (retired vs. unemployed, OR 1.41, p = 0.008). There were no independent associations with Hispanic ethnicity, geographic region, or Social Deprivation Index. Resection was associated with significantly improved survival (median 21 vs. 8 months, p = 0.001). Among resected patients, survival was independently associated with younger age (HR 1.019, p = 0.002), geographic region (South vs. Pacific West, HR 0.721, p = 0.005), and employment (employed vs. unemployed, HR 0.752, p = 0.029). Race, Hispanic ethnicity, marital status, and Social Deprivation Index were not independently associated with survival after resection., Conclusions: Race, marital status, and employment status are independently associated with resection of pancreatic cancer in the VHA, whereas geographic region and employment status are independently associated with survival after resection. Further studies are warranted to determine the basis for these inequities., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Multiple myeloma (MM) is a heterogeneous disease that has an increased incidence in African Americans (AAs). We previously observed that, with equal access to health care, younger AA patients (age < 65 years) have superior overall survival (OS) compared with younger White patients. Because MM prognosis is influenced by 17p deletion (del17p), we investigated racial differences in its occurrence and impact in a large cohort of MM patients from the Veterans Affairs (VA) system. Among 2243 VA patients with MM for whom del17p data were available, del17p was present in 8.83% of all patients, with a significantly lower prevalence in AAs (5.56%) compared with Whites (10.52%; P < .001). The difference was even more pronounced among younger AAs (<65 years) vs younger Whites (4.34% vs 9.8%, respectively; P = .004). However, we did not observe any significant difference in survival between AA and White patients with del17p, regardless of age category, suggesting that del17p carries a poor prognosis across race and age. Interestingly, among patients without del17p, we still noted a significantly superior OS in younger AAs compared with younger Whites (7.75 vs 5.10 years; P = .042). Our study shows a lower incidence of del17p in AAs but suggests that the survival advantage for younger AAs is primarily due to factors other than del17p., (© 2021 by The American Society of Hematology.)

Background: Traditional count-based measures of comorbidity are unlikely to capture the complexity of multiple chronic conditions (multimorbidity) in older adults with cancer. We aimed to define patterns of multimorbidity and their impact in older United States veterans with multiple myeloma (MM)., Methods: We measured 66 chronic conditions in 5076 veterans aged 65 years and older newly treated for MM in the national Veterans Affairs health-care system from 2004 to 2017. Latent class analysis was used to identify patterns of multimorbidity among these conditions. These patterns were then assessed for their association with overall survival, our primary outcome. Secondary outcomes included emergency department visits and hospitalizations., Results: Five patterns of multimorbidity emerged from the latent class analysis, and survival varied across these patterns (log-rank 2-sided P < .001). Older veterans with cardiovascular and metabolic disease (30.9%, hazard ratio [HR] = 1.33, 95% confidence interval [CI] = 1.21 to 1.45), psychiatric and substance use disorders (9.7%, HR = 1.58, 95% CI = 1.39 to 1.79), chronic lung disease (15.9%, HR = 1.69, 95% CI = 1.53 to 1.87), and multisystem impairment (13.8%, HR = 2.25, 95% CI = 2.03 to 2.50) had higher mortality compared with veterans with minimal comorbidity (29.7%, reference). Associations with mortality were maintained after adjustment for sociodemographic variables, measures of disease risk, and the count-based Charlson Comorbidity Index. Multimorbidity patterns were also associated with emergency department visits and hospitalizations., Conclusions: Our findings demonstrate the need to move beyond count-based measures of comorbidity and consider cancer in the context of multiple chronic conditions., (Published by Oxford University Press 2021.)

We completed a pilot study to guide the development of the VA Research Precision Oncology Data Commons infrastructure as a collaboration platform with the greater research community. Our results using a small subset of patients from the VA's Precision Oncology Program demonstrate the feasibility of our data sharing platform to build predictive models for lung cancer survival using machine learning, as well as highlight the potential of target genome sequencing data.