We consider a competing risks setting, when evaluating the prognostic influence of an exposure on a specific cause of failure. Two main regression models are used in such analyses, the Cox cause-specific proportional hazards model and the subdistribution proportional hazards model. They are exemplified in a real data example focusing on relapse-free interval in acute leukaemia patients. We examine the properties of the estimator based on the latter model when the true model is the former. An explicit relationship between subdistribution hazards ratio and cause-specific hazards ratio is derived, assuming a flexible parametric distribution for latent failure times.
Copyright (c) 2006 John Wiley & Sons, Ltd.