Using SEER Data to Quantify Effects of Low Income Neighborhoods on Cause Specific Survival of Skin Melanoma

Background: This study used receiver operating characteristic (ROC) curves to screen Surveillance,Epidemiology and End Results (SEER) skin melanoma data to identify and quantify the effects of socioeconomicfactors on cause specific survival.
Methods: 'SEER cause-specific death classification' used as the outcomevariable. The area under the ROC curve was to select best pretreatment predictors for further multivariateanalysis with socioeconomic factors. Race and other socioeconomic factors including rural-urban residence, countylevel % college graduate and county level family income were used as predictors. Univariate and multivariateanalyses were performed to identify and quantify the independent socioeconomic predictors.
Results: This studyincluded 49,999 parients. The mean follow up time (SD) was 59.4 (17.1) months. SEER staging (ROC area of 0.08)was the most predictive foctor. Race, lower county family income, rural residence, and lower county educationattainment were significant univariates, but rural residence was not significant under multivariate analysis.Living in poor neighborhoods was associated with a 2-4% disadvantage in actuarial cause specific survival.
Conclusions: Racial and socioeconomic factors have a significant impact on the survival of melanoma patients.This generates the hypothesis that ensuring access to cancer care may eliminate these outcome disparities.