Racial differences in carcinoma-in-situ and non-muscle-invasive bladder cancer mortality: Accounting for insurance status, black segregation, and neighborhood poverty.

Abstract

Background: Few Bladder Cancer (BC) studies have examined the role of area-level variables. The purpose of this study was to examine racial differences in BC survival to elucidate if insurance status and contextual covariates could explain Black disadvantage in survival.

Method: Using the Fine-Gray subdistribution hazard models (sHR), five-year survival time was calculated from the date of diagnosis until the last day of follow-up or the date of death due to BC in Florida 2000-2014 (n = 32,321). Non-BC deaths were considered a competing risk. In all models, individual-level clinical and demographic variables were adjusted for and we included the exposures of interest for Carcinoma-in-Situ (CIS) and Non-Muscle-Invasive BC(NMIBC), separately.

Results: In CIS-Patients, living in neighborhoods with higher levels of segregation was associated with 50 % to 2-fold increase in sHR (medium level segregation sHR= 1.50, 95 % CI: 1.06-2.13; high level segregation sHR= 2.07, 95 % CI: 1.25-3.43). Uninsured CIS patients had more than 2-fold increased sHR compared to those with private insurance (sHR=2.34, 95 % CI: 1.05-5.24). In NMIBC patients, living in areas with level of poverty resulted in 10 % the hazard of death increased when compared to low poverty (high poverty sHR=1.11, 95 % CI: 1.01-1.21). Uninsured and Medicaid covered NMIBC patients had an increased sHR (uninsured sHR=2.05, 95 % CI: 1.62-2.59; Medicaid sHR=1.36, 95 % CI: 1.11-1.67). For both CIS and NMIBC patients, the Black/White survival gap decreased when insurance and contextual variables were included.

Conclusion: This study identified BC survival rates were different for Black and White patients in Florida and found that those observed gaps were, to some extent, linked to broader social factors. We recommend that future cancer studies examining racial disparities incorporate area-level variables to offer a more nuanced understanding of these complex disparities.