フリーソフトRを活用した生存データ解析 (総合報告)

Abstract

The Cox's proportional hazards model has been widely used for the analysis of treatment and prognostic effects with censored survival data. The model was developed based on the hazard function for an individual as a fixed-time covariates. When the covariates values change for the duration of the study, however, a number of theoretical problems that are to be solved with respect to the baseline survival function and the baseline cumulative hazard function, are involved. This article presents time-dependent survival data analysis using R which may be evaluated for their impact on survival. We consider how these analyses can affect the prediction of patient outcome using multistate model, stratified Cox's proportional hazard model, and competing risk model.