Impact of socioeconomic disparities on upstaging for prostate cancer: A national cancer database analysis.

Abstract

e17526 Background: Recent data suggest that socioeconomic disparities impact the outcome of oncologic disease. This retrospective analysis investigates the role of socioeconomic variables on clinical to pathologic staging of prostate cancer (PC). Methods: 455,773 males with stage 1-3 adenocarcinoma of prostate who underwent surgical intervention (96% radical prostatectomy) were extracted from the National Cancer Database from 2004-2016. Patients were stratified into age groups based on American Urologic Association PSA screening recommendations ( < 40, 40-54, 55-69, > 70 years). Changes from clinical to pathological staging were the primary outcomes. Demographics, income level, education status and distance to treatment facility ( < 12.5, 12.5-49.9, > 50 miles) were analyzed using Chi-square and logistic regression to find upstaging predictors. Results: Rates of stage changes are summarized in Table. Increased distance ( > 50 vs < 12.5 mi) was associated with upstaging in all age groups (40-54: OR 1.10 95%CI 1.05-1.16; 55-69: OR 1.20 95%CI 1.18-1.23; > 70: OR 1.42 95%CI 1.35-1.50) except for < 40 years (OR 1.15, 95%CI 0.60-2.21). Other predictors of upstaging included black or other race compared to white (OR 1.06 95%CI 1.04-1.09 and OR 1.10 95% CI 1.06-1.14, respectively) and in men with government insurance vs private insurance (OR 1.19 95%CI 1.17-1.21). Lower risk of upstaging was seen for those who were not insured vs private insurance (OR 0.70 95%CI 0.67-0.73), lived in areas with the highest vs lowest high school education rate (OR 0.95, 95%CI 0.92-0.98), or lived in the lowest vs highest income areas (OR 0.93, 95%CI 0.90-0.96). Conclusions: Socioeconomic disparities directly impact the outcome for prostate cancer. Our study suggests age, distance from treatment facility, and race are associated with a greater risk for clinical to pathologic upstaging. Investigation should continue to better understand at-risk populations. [Table: see text]