Abstract
Abstract Purpose. Several factors including, socioeconomic status (SES), access to screening and healthcare coverage, tumor biology, differences in disease management and care delivery in various healthcare settings, and implicit bias among healthcare providers contribute to mortality disparities in individuals with cancer. Further, health insurance is strongly associated with better survival. Previous studies that examined disparities in cancer mortality included patients with and without healthcare coverage, making it difficult to disentangle the effects of health insurance coverage from other SES factors. Thus, we evaluated the influence of race/ethnicity and geocoded SES on all-cause mortality in cancer patients with health insurance. Methods. We identified adults with health insurance coverage diagnosed with eight common cancers from 2009 to 2014 from the California Cancer Registry (stages I-IV) and followed them through 2017 (8 years maximum). Specifically, we identified those who lived in southern California counties. Patients had managed care, preferred provider organization, Medicare, Medicaid, dual Medicare and Medicaid, and other private insurance. We calculated person-year mortality rates by race/ethnicity and geocoded SES quintiles. Adjusted hazard ratios for the association between overall mortality and race/ethnicity and SES were estimated using Cox proportional hazards models accounting for other demographics, stage at diagnosis, and cancer treatments. Results. 164,197 adults were diagnosed with cancer originating from breast, prostate, lung, colon, skin melanoma, uterus, kidney, and bladder. For all racial/ethnic groups combined, the mortality rates from lowest to highest SES groups were 112.1/1000 PY (lowest); 100.2/1000 PY (lower-middle); 91.2/1000 PY (middle); 79.1/1000 PY (upper-middle); and 63.5/1000 PY (upper). These rates suggest that people with the lowest SES have a markedly increased mortality risk after cancer diagnosis even if they have health insurance. In multivariable analyses, those in the lowest SES group had a 40–78% increased risk of all-cause mortality compared to those in the upper SES group across all races/ethnicities. For example, within African Americans, the adjusted mortality risk was up to 61% higher (HR 1.61, 95% CI 1.41–1.83) in the lowest SES group compared to the highest SES group. Conclusion. This study suggests disparities in overall mortality risk after cancer diagnoses persist even in a cohort with health insurance, and that SES is an important driver of this disparity. Issues related to travel distance, access to transportation to cancer care facilities, and access to telemedicine may be magnified among those with lower SES during cancer care where optimal management becomes more complex. To potentially mitigate the effects of these social determinants, healthcare systems must either implement programs to support patients, or have partnerships with local community organizations to do so. All of this requires systems level support through social work, patient navigation, and cancer case management. Citation Format: Reina Haque, Amrita Mukherjee, Robert M. Cooper. Patterns of mortality risk in insured patients with cancer by race/ethnicity and socioeconomic status in Southern California [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C127.
Published Version
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