Impact of social determinants of health on mortality in diffuse large B-cell lymphoma (DLBCL) using real-world data.

Abstract

11097 Background: Treatment advances in DLBCL have led to remarkable improvements in patient outcomes. Social determinants of health (SDOH) can contribute to inequities in outcomes in multiple cancer types, and there is a paucity of studies evaluating their impact in DLBCL. Methods: We used the nationwide Flatiron Health electronic health record derived de-identified database and included adults with a confirmed diagnosis of DLBCL from 2011-2024 to evaluate the association between SDOH and real-world overall survival (from time of initial treatment). Area-level SDOH variables were derived from the Census Bureau’s American Community Survey and the 2019 AHRQ’s SDOH database. These census tract level measures were grouped into US population-weighted quartiles and evaluated across the following domains: economic, social (including racial segregation), neighborhood & physical environment, and healthcare. We estimated adjusted hazard ratios (aHR) for the highest social deprivation quartile (least resourced areas) compared to the lowest quartile using Cox proportional hazard models, adjusting for age, sex, race/ethnicity, LDH, ECOG, presence of extranodal disease, stage, and cell of origin. Results: We included 6,855 patients in the analysis. After adjustment, residence in areas with the highest social deprivation was consistently associated with increased mortality across all SDOH domains compared with the lowest deprivation areas. A higher risk of death (> 20%) was found for patients residing in predominantly Black vs. White neighborhoods, those residing in medically underserved areas, and areas with the lowest levels of private insurance. Similarly, residence in areas with the least access to the internet, computing devices, and cellular data plans was associated with increased mortality risk. Conclusions: Higher SDOH deprivation was significantly associated with increased mortality among patients with DLBCL, despite controlling for demographic and clinical factors. The SDOH influencing mortality ranged from socioeconomic and technological inequities to limited healthcare access and racial segregation. These factors may aid improved prognostication of DLBCL, and future studies should focus on developing interventions to mitigate SDOH-linked inequities in DLBCL. aHR 95% CI Domain Households that received food stamps/SNAP 1.15 1.02, 1.29 Economic Households with no internet access 1.15 1.02, 1.29 Neighborhood Households without a computing device 1.12 1.00, 1.26 Physical Households without cellular data plan 1.13 1.00, 1.26 Environment Medically underserved area 1.20 1.02, 1.40 Healthcare Population private health insurance (≤ 64) 1.24 1.10, 1.39 Population TRICARE/military/ VA insurance only (≤64) 1.17 1.05, 1.30 Population no health insurance (≤64) 1.18 1.06, 1.33 Residential Segregation Blacks (reference: Whites) 1.23 1.01, 1.51 Social