Disparities in ovarian cancer care quality and survival according to race and socioeconomic status

Abstract

Background The relationship between racial and socioeconomic status (SES) disparities and the quality of epithelial ovarian cancer care and survival outcome are unclear. Methods A population-based analysis of National Cancer Data Base (NCDB) records for invasive primary epithelial ovarian cancer diagnosed in the period from 1998 to 2002 was done using data from patients classified as white or black. Adherence to National Comprehensive Cancer Network (NCCN) guideline care was defined by stage-appropriate surgical procedures and recommended chemotherapy. The main outcome measures were differences in adherence to NCCN guidelines and overall survival according to race and SES and were analyzed using binomial logistic regression and multilevel survival analysis. Results A total of 47 160 patients (white = 43 995; black = 3165) were identified. Non-NCCN-guideline-adherent care was an independent predictor of inferior overall survival (hazard ratio [HR] = 1.43, 95% confidence interval [CI] = 1.38 to 1.47). Demographic characteristics independently associated with a higher likelihood of not receiving NCCN guideline-adherent care were black race (odds ratio [OR] = 1.36, 95% CI = 1.25 to 1.48), Medicare payer status (OR = 1.20, 95% CI = 1.12 to 1.28), and not insured payer status (OR = 1.33, 95% CI = 1.19 to 1.49). After controlling for disease and treatment-related variables, independent racial and SES predictors of survival were black race (HR = 1.29, 95% CI = 1.22 to 1.36), Medicaid payer status (HR = 1.29, 95% CI = 1.20 to 1.38), not insured payer status (HR = 1.32, 95% CI = 1.20 to 1.44), and median household income less than $35 000 (HR = 1.06, 95% CI = 1.02 to 1.11). Conclusions These data highlight statistically and clinically significant disparities in the quality of ovarian cancer care and overall survival, independent of NCCN guidelines, along racial and SES parameters. Increased efforts are needed to more precisely define the patient, provider, health-care system, and societal factors leading to these observed disparities and guide targeted interventions. © 2013 The Author.