No abstract

Esophageal cancer is the seventh most common type of cancer in the world, the sixth leading cause of cancer-related death and its incidence is expected to rise 140% in the world in a period of 10 years until 2025. The overall incidence is higher in males, while data about prognosis and survival are not well established yet. The goal of this study was to carry out a comprehensive analysis of differences between sexes and other covariates in patients diagnosed with primary esophageal cancer. Data from 2005 to 2020 were obtained from the University Hospitals (UH) Seidman Cancer Center and from 2005 to 2018 from SEER. Patients were categorized according to histological subtype and divided according to sex. Pearson Chi-square test was used to compare variables of interest by sex and the influence of sex on survival was assessed by Kaplan Meier, log rank tests and Cox proportional hazards regression models. A total of 1205 patients were used for analysis. Sex differences in all types were found for age at diagnosis, histology, smoking status and prescriptions of NSAIDs and in SCC for age at diagnosis and alcoholism. Survival analysis didn’t showed differences between males and females on univariable and multivariable models. Males have a higher incidence of Esophageal Cancer and its two main subtypes but none of the comprehensive set of variables analyzed showed to be strongly or unique correlated with this sex difference in incidence nor are they associated with a sex difference in survival.

Background: Racial disparities have been reported for breast cancer and cardiovascular disease (CVD) outcomes. The determinants of racial disparities in CVD outcomes are not yet fully understood. We aimed to examine the impact of individual and neighborhood-level social determinants of health (SDOH) on the racial disparities in major adverse cardiovascular events (MACE; consisting of heart failure, acute coronary syndrome, atrial fibrillation, and ischemic stroke) among female patients with breast cancer. Methods: This 10-year longitudinal retrospective study was based on a cancer informatics platform with electronic medical record supplementation. We included women aged ≥18 years diagnosed with breast cancer. SDOH were obtained from LexisNexis, and consisted of the domains of social and community context, neighborhood and built environment, education access and quality, and economic stability. Race-agnostic (overall data with race as a feature) and race-specific machine learning models were developed to account for and rank the SDOH impact in 2-year MACE. Results: We included 4,309 patients (765 non-Hispanic Black [NHB]; 3,321 non-Hispanic white). In the race-agnostic model (C-index, 0.79; 95% CI, 0.78–0.80), the 5 most important adverse SDOH variables were neighborhood median household income (SHapley Additive exPlanations [SHAP] score [SS], 0.07), neighborhood crime index (SS = 0.06), number of transportation properties in the household (SS = 0.05), neighborhood burglary index (SS = 0.04), and neighborhood median home values (SS = 0.03). Race was not significantly associated with MACE when adverse SDOH were included as covariates (adjusted subdistribution hazard ratio, 1.22; 95% CI, 0.91–1.64). NHB patients were more likely to have unfavorable SDOH conditions for 8 of the 10 most important SDOH variables for the MACE prediction. Conclusions: Neighborhood and built environment variables are the most important SDOH predictors for 2-year MACE, and NHB patients were more likely to have unfavorable SDOH conditions. This finding reinforces that race is a social construct.

Introduction: Cardiovascular disease (CVD) prevalence and cancer mortality are higher in non-Hispanic Blacks (NHB) relative to other racial subpopulations. Hypothesis: Among females with BC (≥18 years), there are racial differences in cardiac events (CEV) which can be explained by adverse social determinants of health (SDOH). Methods: Data were obtained from a Cleveland area integrated health care systems informatics platform. (2005-2019). Zip-code level demographic features were extracted using the SDOH Database from the Agency for Healthcare Research and Quality. The CEVs included were heart failure (HF), acute coronary syndrome (ACS), and ischemic stroke (IS). Multivariable Cox proportional hazards regression models were used to examine racial disparities in CEVs. Race-stratified (NHB and non-Hispanic Whites [NHW]) multivariable logistic regression was performed to assess the role of each SDOH in association with CEV. Results: This study included 9,022 females with breast cancer (BC) of which 18.8% were NHB, and 48.7% had a CEV. The racial differences in CEV and the role of zip-code level SDOH are presented in Table 1. These racial differences were not explained by the proportion of people unemployed in the zip code (p=0.42, race*unemployment % [cross-product]), proportional of people in the zip code with only a high school diploma (p=0.66, race*education % [cross-product]), and proportion of people in the zip code who use public transport (p=0.24, race * transport % [cross-product]). Conclusion: There are racial differences in the risk of ACS and IS after a BC diagnosis, but this does not seem to be explained by the 3 adverse zip-code level SDOH included in this study. Therefore, studies with individual-level SDOH and including other domains are necessary to better understand their relationship with CEVs.