African-American Race and Low-Income Neighborhoods Decreased Cause-Specific Survival of Endometrial Cancer: A SEER Analysis

Abstract

Purpose/Objective(s)This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact endometrial cancer survival.Materials/MethodsEndometrial cancer patients treated from 2004 to 2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data was analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors.ResultsThis study included 64,710 patients. The mean follow-up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 12% and 2%, respectively.ConclusionsThis study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes. Purpose/Objective(s)This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact endometrial cancer survival. This study analyzed Surveillance, Epidemiology and End Results (SEER) data to assess if socio-economic factors (SEFs) impact endometrial cancer survival. Materials/MethodsEndometrial cancer patients treated from 2004 to 2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data was analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors. Endometrial cancer patients treated from 2004 to 2007 were included in this study. SEER cause specific survival (CSS) data were used as end points. The areas under the receiver operating characteristic (ROC) curve were computed for predictors. Time to event data was analyzed with Kaplan-Meier method. Univariate and multivariate analyses were used to identify independent risk factors. ResultsThis study included 64,710 patients. The mean follow-up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 12% and 2%, respectively. This study included 64,710 patients. The mean follow-up time (S.D.) was 28.2 (20.8) months. SEER staging (ROC area of 0.81) was the best pretreatment predictor of CSS. Histology, grade, race/ethnicity and county level family income were also significant pretreatment predictors. African American race and low income neighborhoods decreased the CSS by 12% and 2%, respectively. ConclusionsThis study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes. This study has found significant endometrial survival disparities due to SEFs. Future studies should focus on eliminating socio-economic barriers to good outcomes.