Statistical modeling of CALGB 80405 (Alliance) to identify influential factors in metastatic colorectal cancer (CRC) dependent on primary (1o) tumor side.

3528Background: CALGB 80405 is a phase III clinical trial of FOLFOX and FOLFIRI w/ randomly assigned cetuximab or bevacizumab. Novel machine learning approaches to the study dataset provide valuable insights into CRC prognosis and management of CRC progression. Methods: Using a Monte Carlo Bayesian Generalized Linear Model analytical platform, we built an ensemble of models for overall survival (OS). We used 99 baseline and demographic variables, including 1904 patients w/ 1o side and 949 w/ KRAS wild-type status. Building an ensemble of predictive models reduces risk of overfitting, estimates model uncertainty and identifies key variables by model consensus as measured by ensemble frequency (freq). We fit gender and 1o side (L vs R) stratum-specific models to examine differences in drivers of disease in those strata. Results: 1o side (avg Cox hazard ratio = 0.89, R side reference), ECOG performance status (1.30, reference level 0), AST concentration (1.01), peripheral neutrophil percentage (1.01) and loc...