Abstract
Introduction: We conducted the first known nationally representative propensity score analysis of racial and income inequities in cardiovascular disease (CVD) for patients with and without active cancer. Methods: Propensity score adjusted and backward propagation neural network machine learning augmented multivariable regression was performed by race and income (and their interaction) for the above outcomes in this case-control study of the United States’ largest and first ICD10-coded all-payer hospitalized dataset, the 2016 National Inpatient Sample (NIS). Models were stratified by active cancer and CVD (defined by the 2021 WHO). Results: Of the 30,195,722 adult hospitalized patients, 25.64% had CVD, and 7.11% had active cancer. In fully adjusted regression among patients without cancer, Hispanic (OR 1.34, 95%CI 1.03-1.25; p=0.012) and Asian (OR 1.22; 95%CI 1.11-1.34; p<0.001) had significantly increased mortality compared to Caucasian patients as did the lowest (OR 1.11; 95%CI 1.07-1.15; p<0.001) and second lowest (OR 1.05; 95%CI 1.01-1.08; p=0.006) income quartiles compared to the highest. Among patients with cancer, similar significant racial inequities were noted but without income disparities. Mortality was not significantly increased by the interaction in either strata. Among patients without cancer, Hispanics ($14,196.68; 95%CI 12,887.86-15,505.51; p<0.001) and Asians ($19,377.06; 95%CI 17,939.38-20,814.74; p<0.001) had significantly increased costs compared to Caucasians; African American, Hispanic, and Asian patients in the lowest and second lowest income quartiles had significantly increased costs compared to Caucasians in the highest quartile. Patients with cancer had comparable cost inequities by race but not by income or the interaction. Conclusions: This nationally representative study suggests that significant income and racial inequities exist in inpatient mortality and cost among patients with CVD, though these disparities are less pronounced among cancer versus non-cancer patients.
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