Estimating Time-Varying Effects of Prognostic Factors for Stomach Cancer Patients within a Dynamic Grouped Cox Model

We describe the identification of prognostic factors in the framework of a completely resected stomach cancer survival-study. For the analysis the dynamic grouped Cox-Model was used allowing for time-varying covariate effects. Therefore the hazard rate might be non-proportional. As estimation concept we applied the posterior mode, computed by iteratively weighted Kalman filtering and smoothing steps. The medical study and questions are described, the statistical method is illustrated, the results are given and interpreted and the method is discussed.