Guha, Avirup

This cohort study examines patterns of bone-modifying agent use from 2013 to 2024 among men with metastatic castration-resistant prostate cancer.

352 Background: Glucagon-like peptide 1 (GLP1) receptor expression in prostate cancer tissue has raised concerns that GLP1 receptor agonists (GLP1A) may influence tumor growth or progression. We compared prostate cancer severity at diagnosis among patients receiving GLP1A versus other glucose lowering therapies. Methods: A retrospective chart review identified patients who received GLP1A or alternative second-line glucose lowering agents (DPP4/SGLT2 inhibitors) and were subsequently diagnosed with prostate cancer. Patients receiving both drug classes were excluded. Baseline demographics (race, ethnicity, age), comorbidities (diabetes, myocardial infarction, peripheral vascular disease) concomitant medications (insulin, metformin, statins), appointments (within past year) and laboratory values (HbA1c, eGFR) at therapy initiation were recorded. Primary outcomes included Gleason grade group and metastatic presentation within three months of diagnosis. Propensity score matching balanced baseline characteristics between groups. Mann-Whitney U tests compared grade groups. Chi-square tests compared metastatic presentation, reporting odds ratios (OR) with 95% confidence intervals (CI). Multivariable logistic regression identified predictors of grade group (low-grade: 1-2; high-grade: ≥3) and metastatic presentation, reporting OR with 95% CI. A p value <0.05 indicated a significant association. Results: Of 260 propensity-matched patients (GLP1A: 130, comparison: 130), 87% were White and 95% were Non-Hispanic/Non-Latino in each group. Median HbA1c was 7% (IQR: 6.4-8) in GLP1A group versus 7.5% (6.2-8.5) in comparison group. Median eGFR was 75mL/min/1.73m 2 (IQR: 61.5-90.0) in GLP1A group versus 60.0 (52.0-80.5) in comparison group. High-grade disease occurred in 33 (25%) GLP1A patients and 37 (29%) comparison patients. Among patients with available imaging (GLP1A: 40; comparison: 32), metastatic presentation occurred in 7 (18%) GLP1A group and 7 (22%) comparison group patients. No significant differences were observed in grade group (GLP1A median: 2; IQR: 1-2 vs. comparison median: 2; 1-3; p=0.44) or metastatic presentation (OR: 1.32; 95%CI: 0.41-4.25; p=0.64) between groups. In multivariable analysis, higher HbA1c was associated with high-grade disease in GLP1A group (OR: 1.83; 95%CI: 1.07-3.35; p=0.03) while higher eGFR was associated with low-grade disease in the comparison group (0.97; 0.93-0.99; p=0.04). Conclusions: GLP1A use was not associated with prostate cancer grade or metastatic presentation at diagnosis compared to alternative glucose-lowering agents. However, the association between elevated HbA1c and high-grade disease in GLP1A patients suggests a potential impact of poor glycemic control on tumor biology. Prospective studies are needed to elucidate the relationship between metabolic dysregulation and prostate cancer severity.

Abstract Background Socioeconomic position (SEP) is a fundamental social determinant of health (SDoH) contributing to observed disparities in cancer and cardiovascular (CV) care among individuals with prostate cancer (PC). Understanding the influence of SEP on CV health is essential for addressing outcome inequities within this population. Methods We conducted a retrospective study utilizing Surveillance, Epidemiology, and End Results (SEER)-Medicare to evaluate CV outcomes in patients ≥65 years with PC from 2009 to 2017. We studied the impact of SEP on cardiovascular events (CVEs), cardiovascular mortality (CVm), PC-specific mortality (PCsm), and all-cause mortality. CVE, CVm, and PCsm were analyzed using competing risk models and all-cause mortality with Cox proportional hazards models. A subgroup analysis was performed in Non-Hispanic Black and Non-Hispanic White individuals. Results We included 141 242 patients of whom 76 844 were in high SEP areas (45.6%) and 64 398 in low SEP ones (54.4%). Both groups had a mean age of 72 years; patients in low SEP areas were 67.5% Non-Hispanic White, 34.4% having diabetes, 73.3% hypertension, and 67.7% dyslipidemia versus the high SEP group with 85.6% Non-Hispanic White, 30.4% diabetes, 69.9% hypertension, and 70.7% dyslipidemia. Patients in low SEP areas had higher risks of CVm (subdistribution hazard ratio [sHR] = 1.18, 95% CI = 1.12 to 1.25), PCsm (sHR = 1.12, 95% CI = 1.06 to 1.17), CVE (sHR = 1.07, 95% CI = 1.04 to 1.09), and all-cause mortality (HR 1.16, 95% CI = 1.13 to 1.20). Accentuated results were shown in the Non-Hispanic Black subgroup. Conclusion Adverse SEP plays a significant role in shaping outcomes among older patients with PC, contributing to elevated risks of adverse CV and survival outcomes.

Abstract Aims We aimed to perform a retrospective cohort study using the Centers for Disease Control and Prevention’s (CDC’s) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database to analyse the trends in cardiovascular disease (CVD)–related mortality in patients with myeloproliferative neoplasms (MPNs) from 1999 to 2020. Methods and results We analysed the death certificate data from the CDC WONDER database from 1999 to 2020 for CVD with co-morbid myeloproliferative disorders in the US population. Age-adjusted mortality rates (AAMRs) and 95% confidence intervals (CIs) were computed per 1 million population by standardizing crude mortality rates to the 2000 US census population. To assess annual national mortality trends, we employed the Joinpoint regression model, calculating the annual per cent change in AAMR and corresponding 95% CIs. A total of 15 269 deaths related to CVD occurred in patients with co-morbid MPNs from 1999 to 2020. Overall, there was a decreasing trend in CVD-related AAMRs throughout these years. Males contributed to 51% of total deaths, and their AAMR was persistently higher than women throughout the study. Non-Hispanic (NH) Whites had the highest overall AAMR, followed by NH Blacks, NH American Indians or Alaska Natives, Hispanics or Latinos, and NH Asian or Pacific Islanders. Conclusion Our findings indicate a significant decline with notable gender, racial/ethnic, and regional differences in CVD-related mortality among patients with MPN over the past two decades. We emphasize the importance of a collaborative approach between oncologists and cardiologists in managing these patients, highlighting the potential benefits of integrating cardio-oncology services to enhance patient outcomes.

314 Background: Prostate cancer patients (PC) face an elevated risk of both developing atherosclerotic cardiovascular disease (ASCVD). The American College of Cardiology Pooled Cohort Equations (PCE) for ASCVD predictions may lack accuracy. Methods: Males ≥18 years, diagnosed with PC between 2005-2012 at a hybrid academic-community practice were included. Using XGBoost algorithm we developed using a training subset of the cohort (50% train + 25% test), ranked 33 covariates (including demographic, treatment-related and social determinants of health (SDOH) information) for ASCVD prediction using SHAP (Shapley additive explanations) values. The top 10 predictors were transformed in a predictive equation using logistic regression models. This equation was tested in the cohort validation subset (25%), and subsequently compared to the PCE risk score. Results: We included 1,506 patients, with a median age of 67 (IQR 60-74) years, 13.8% had advanced stage disease (TNM III-IV), 1.5% had high risk PC (Gleason 8-10), and 20.5% received androgen deprivation therapy (ADT). Of those, 10.4% had a 10-year ASCVD risk. The PCE had an area under the curve (AUC)=0.61 and underestimated ASCVD in 0.9% (mean risk=20.1% [95% CI 17.2-23.0] vs. mean predicted risk=19.2% [95% CI 18.6-19.8]). The equation pooled from the top-10 predictors of the ML algorithm (C-index=0.78 [95% CI 0.75-0.81]) achieved an AUC=0.71 (Table). Conclusions: Conventional PCE tend to underestimate ASCVD risk in males with PC. A cancer-specific model inclusive of SDOH exhibits good performance for predicting ASCVD risk in this population. [Table: see text]

BACKGROUND: Global collaboration in cardio-oncology is needed to understand the prevalence of cancer therapy-related cardiovascular toxicity in different risk groups, practice settings, and geographic locations. There are limited data on the socioeconomic and racial/ethnic disparities that may impact access to care and outcomes. To address these gaps, we established the Global Cardio-Oncology Registry, a multinational, multicenter prospective registry. METHODS: We assembled cardiologists and oncologists from academic and community settings to collaborate in the first Global Cardio-Oncology Registry. Subsequently, a survey for site resources, demographics, and intention to participate was conducted. We designed an online data platform to facilitate this global initiative. RESULTS: A total of 119 sites responded to an online questionnaire on their practices and main goals of the registry: 49 US sites from 23 states and 70 international sites from 5 continents indicated a willingness to participate in the Global Cardio-Oncology Registry. Sites were more commonly led by cardiologists (85/119; 72%) and were more often university/teaching (81/119; 68%) than community based (38/119; 32%). The average number of cardio-oncology patients treated per month was 80 per site. The top 3 Global Cardio-Oncology Registry priorities in cardio-oncology care were breast cancer, hematologic malignancies, and patients treated with immune checkpoint inhibitors. Executive and scientific committees and specific committees were established. A pilot phase for breast cancer using Research Electronic Data Capture Cloud platform recently started patient enrollment. CONCLUSIONS: We present the structure for a global collaboration. Information derived from the Global Cardio-Oncology Registry will help understand the risk factors impacting cancer therapy-related cardiovascular toxicity in different geographic locations and therefore contribute to reduce access gaps in cardio-oncology care. Risk calculators will be prospectively derived and validated.

Introduction: Heart Disease and Stroke Statistics_2014 Update suggests more than 424,000 people suffer out of hospital cardiac arrest (OHCA) in the United States. Hypothesis: We assessed seasonal variation in OHCA from a large national hospitalisation database in the past decade. Methods: The Nationwide Inpatient Sample database was used to estimate the annual number of hospitalisations with from 2000-2011. Identification of out of hospital cardiac arrest related hospitalisations was based on the designation of the International Classification of Diseases (9th Edition) Clinical Modification (ICD-9-CM) diagnosis code 427.5 (OHCA) as the principal discharge diagnosis. The frequency of hospitalisation for each month cumulative over 11 years was calculated and divided by number of days in that month to obtain the mean hospitalisations per day for each month. All calculations were carried out using the weighted estimates approximating nationwide population estimates. Results: An estimated 93,209 hospitalisations with primary diagnosis of OHCA occurred in the United States from the beginning of the calendar year 2000 to the end of the calendar year 2011. The number of hospitalisations per day in each month is shown in Figure 1.The number of hospitalisation was maximum in the winter months and minimum in summer months. Specifically, the mean number of hospitalisation each day (averaged over 11 years) was least in August (242). There was a rising trend from August to January. The average number of hospitalisation was highest in January (310); thereafter, the hospitalisation rate dropped to a nadir in August. There was however no seasonal pattern in inhospital mortality. Conclusions: We identified for the first time in United States an impressive pattern of seasonal variation in hospitalisations for OHCA. Further efforts must be made to identify triggers and methods to prevent OHCA and reduce its burden on health care system.