Socio-economic Status, Patterns of Care, and Survival Times in a Supportive Oncology Cohort Público
Armstrong, Karen (Fall 2017)
Abstract
Research suggests that disparities in all-cause cancer survival times include a dynamic interplay of Socio-economic status (SES) and patterns of care. The purpose of this study was to examine survival times and patterns or care among SES strata within a supportive oncology cohort at a large academic medical center.
After obtaining IRB approval, a retrospective chart review of medical records from 2013-2017 was conducted. The sample (n=4495) of adult cancer patients was 50% female, 51% white, and mostly (81%) high SES position. The mean age was 66.24 years (SD=15.23). Treatment patterns included 596 (14%) chemotherapy, 402 (9%) radiation, 415 (9%) both chemotherapy and radiation; and 3015 (68% ) reported not having any treatment. Median survival time was 12.88 days. Over 95% of sample reported multiple comorbidities while 76% reported enrollment in government insurance. Based on the conventional result, high SES patients were more likely to have treatment compared to the low SES patients (OR= 1.64; confidence interval 1.24, 1.99). We conducted a bias analysis to address potential threats to validity of the study. Conditional on the accuracy of the bias-adjusted model, high SES patients were 4.54 times more likely to receive treatment compared to low SES patients. After controlling for age, sex, race, co-morbidities, SES, and insurance status, hazard of mortality between those with no cancer treatment was HR=1.03 (0.96, 1.11) times the corresponding hazard among those receiving treatment. Our findings, taken in context with those of previous studies, suggest that patients with higher SES are more likely to receive chemotherapy and/or radiation compared to their low SES counterparts although we did not observe real differences in survival times between treatment groups. We need further investigation to examine the effect of SES, in combination with other psychosocial variables, to obtain valid estimates of the association between SES and survival times.
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