Background: This study used Surveillance, Epidemiology and End Results (SEER) pancreatic cancer datato identify predictive models and potential socio-economic disparities in pancreatic cancer outcome. Materialsand
Methods: For risk modeling, Kaplan Meier method was used for cause specific survival analysis. TheKolmogorov-Smirnov’s test was used to compare survival curves. The Cox proportional hazard method wasapplied for multivariate analysis. The area under the ROC curve was computed for predictors of absolute riskof death, optimized to improve efficiency.
Results: This study included 58,747 patients. The mean follow up time(S.D.) was 7.6 (10.6) months. SEER stage and grade were strongly predictive univariates. Sex, race, and threesocio-economic factors (county level family income, rural-urban residence status, and county level educationattainment) were independent multivariate predictors. Racial and socio-economic factors were associated withabout 2% difference in absolute cause specific survival.
Conclusions: This study s found significant effects ofsocio-economic factors on pancreas cancer outcome. These data may generate hypotheses for trials to eliminatethese outcome disparities.