Key points are not available for this paper at this time.
Chronic medical conditions are often manifested by the incidence of recurrent adverse clinical events. In clinical trials designed to investigate therapeutic interventions for such conditions it is natural to make treatment comparisons on the basis of event occurrence. However, when there is a more serious, possibly related, event that terminates the occurrence of the recurrent events, the problem of dependent censoring arises. Here, we consider robust modelling strategies for expressing covariate effects on the recurrent event process that address the possible dependence between the recurrent and terminal events. The various methods differ in the way the dependence is addressed, and hence in the interpretation of covariate effects. The methods are applied to a data set from a kidney transplant study and simulated data chosen for illustrative purposes.
Cook et al. (Wed,) studied this question.