Estimation of the time-dependent AUC for cure rate model with covariate dependent censoring

Diverse methods to evaluate the prediction model of a time to event have been proposed in the context of right censored data where all subjects are subject to be susceptible.A time-dependent AUC (area under curve) measures the predictive ability of a marker based on case group and control one which are varying over time.When a substantial portion of subjects are event-free, a population consists of a susceptible group and a cured one.An uncertain curability of censored subjects makes it difficult to define both case group and control one.In this paper, our goal is to propose a time-dependent AUC for a cure rate model when a censoring distribution is related with covariates.A class of inverse probability of censoring weighted (IPCW) AUC estimators is proposed to adjust the possible sampling bias.We evaluate the finite sample performance of the suggested methods with diverse simulation schemes and the application to the melanoma dataset is presented to compare with other methods.