Estimation of change-point in the covariate effects on restricted mean survival time

The restricted mean survival time (RMST) emerges as a crucial summary metric in survival analysis. In some cases, certain covariates may have a varying impact on RMST at one specific change-point. For instance, consider studies focusing on women’s health, where a notable shift in a patient’s lifespan might occur when the age at menopause surpasses a particular cutoff value. To tackle this complex phenomenon, we consider a regression analysis of RMST with change-point in the covariate effects. This involves building a generalized linear model that directly captures the relationship between RMST and associated covariates that may have a change-point. Using the smoothed estimating equation with pseudo-observations, we obtain parameter estimators and establish the large sample properties. Finally, we assess the finite sample performance of the proposed method through simulation studies and apply it to real data examples from primary biliary cirrhosis and rectal cancer studies.