Patient demographic characteristics and disease stage as drivers of disparities in mortality in prostate cancer patients who receive care at a safety net academic medical center.

Introduction: The purpose of this study was to examine the effect of patient demographic characteristics and tumor stage at diagnosis on mortality in prostate cancer patients who receive care at a safety net, academic medical center with a diverse patient population.

Patients And Methods: Eight hundred sixty-nine patients were diagnosed with prostate cancer at our institution between August 2004 and October 2011. Patient demographic characteristics were determined as follows: race and/or ethnicity, primary language, insurance type, age at diagnosis, marital status, income (determined by zip code), and American Joint Committee on Cancer (AJCC) tumor stage. Fisher exact or Pearson χ(2) test was used to test for differences in categorical variables. Multivariate logistic regression analysis was performed to identify factors related to mortality recorded at the end of follow-up in March of 2012.

Results: Mortality was significantly decreased in patients who spoke Haitian Creole (odds ratio [OR], 0.18; 95% confidence interval [CI], 0.04-0.74; P = .017). Distribution of insurance type, age, income, and prostate-specific antigen level differed between English and Haitian Creole speakers. Increased mortality was observed in patients who were single (OR, 1.99; 95% CI, 1.06-3.73; P = .032), older than 70 (OR, 15.5; 95% CI, 3.03-79.45; P = .001), had Medicaid and/or free care (OR, 4.98; 95% CI, 1.72-14.4; P = .003), or had AJCC stage IV cancer (OR, 9.56; 95% CI, 4.89-18.69; P < .001). There was no significant difference in mortality according to race and/or ethnicity or income in the multivariate-adjusted model.

Conclusion: In this retrospective study, prostate cancer patients who spoke Haitian Creole had a lower incidence of mortality compared with English speakers. Consistent with similar large-scale studies, being single or having Medicaid and/or free care insurance predicted worse outcomes, reinforcing their roles as drivers of disparities.