Statistical analysis

Place: WMAX 110, West Mall, UBC

Semi-competing risks data frequently arise in clinical and observational studies. In these cases, the subject can experience both non-terminal and terminal events where the terminal event (e.g., death) censors the non-terminal event (e.g., relapse) but not vice-versa. Typically, the two events are correlated. An approach based on latent failure times has been advocated for the analysis of such data, where the joint survival function of two event times is assumed to follow a copula function over the positive quadrant with observation restricted to the upper wedge. We argue, that similar to models for competing risks, latent failure times should generally be avoided in modeling such data. We consider an illness-death process which circumvents any need for latent times and provides for easy incorporation of covariates. Nonparametric maximum likelihood estimation is used for inference, a simple iterative procedure is developed and needed asymptotic results are obtained. Simulation studies are conducted to assess the finite sample performance of the proposed estimators and the methods are illustrated in an analysis of data on nasopharyngeal cancer from a randomized clinical trial in Singapore.