Guha, Avirup

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: Non-Hodgkin lymphoma (NHL) survivors are at increased risks of cardiovascular disease related death (CVD) compared to the general population. Objective: This study sought to determine the longitudinal trends in mortality attributed to CVD with comorbid NHL by race, sex, and geographic location. Methods: We queried the Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research database among patients aged 18 and above from 1999 to 2020. Patients were identified when the primary causes of death were ischemic heart diseases (ICD 10 I20-I25), cerebrovascular diseases (I60-I69), or hypertensive disease (I10-I15), and NHL (C82-C85) was a contributing cause of death. We calculated age-adjusted mortality rates (AAMRs) per 1,000,000 individuals and determined the trends over time by estimating the annual percent change using the Joinpoint regression program. Results: In the 22-year study period, a total of 22,778 CVD with comorbid NHL were identified. Overall, there was a significant decrease in annual trends for the AAMRs of CVD from 6.91 per 1,000,000 individuals in 1999 to 4.12 per 1,000,000 individuals in 2020 (p<0.05), with an annual percent decrease of 3.3. Overall, men recorded a higher AAMRs compared to women (6.76 vs 3.45, p<0.05). When stratified by race, White individuals had the highest AAMRs (5.07), while the AAMRs for American African, Asian, American Indian individuals were 3.01, 2.77, and 2.48 per 1,000,000 individuals respectively. The AAMRs were higher in the rural region than in the urban region (4.97 vs 4.78, p<0.05). Among all consensus regions, South region had the highest AAMRs. Conclusion: In conclusion, our study revealed a significant decrease in cardiovascular disease related deaths with comorbid NHL over the past two decades. It provides valuable insights into the effectiveness of management of comorbid CVD or CVD risk factors in patients with NHL.

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.