Predictive survival model with time-dependent prognostic factors: development of computer-aided SAS Macro program

Aims and objectives Computer program for the prediction of survival with respect to time‐dependent proportional hazards regression model has been rarely addressed. We therefore developed a SAS Macro program for time‐dependent Cox regression predictive model for empirical survival data associated with time‐dependent covariates. Method Time‐dependent proportional hazards regression model and partial likelihood in association with time‐varying predictors were explicitly delineated. Baseline hazard using Andersen's method was incorporated into proportional hazards regression model to predict the dynamic change of cumulative survival in respect of time‐varying predictors. Two SAS Macro programs for time‐dependent predictive survival model and model validation using receiver operative characteristics were written with SAS IML language. Results The computer program was applied to data on clinical surveillance of small hepatocellular carcinoma (HCC) treated by percutaneous ethanol injection (PEI) or transcatheter arterial embolization (TAE) with time‐varying predictors such as alpha‐feto protein (AFP) and other biological markers. Conclusion The program is very useful for real‐time prediction of cumulative survival on the basis of time‐dependent covariates.