Interim monitoring of longitudinal comparative studies with recurrent event responses

A method of interim monitoring is described for longitudinal comparative studies in which the outcome of interest is a recurrent event and treatment comparisons are based on expected numbers of events. The nonparametric methods described by Cook, Lawless, and Nadeau (1996, Biometrics 52, 116-130) are generalized to provide a robust estimate of the covariance matrix for a sequence of test statistics calculated over time. The error spending function methodology of Lan and DeMets (1983, Biometrika 70, 659-663) is adopted to control the experimental type I error rate. A simulation study indicates satisfactory frequency properties of this procedure for the moderate to large scale trials for which it is intended. Extensions of this approach to handle stratified designs and studies with multitype recurrent events are indicated. Data from a kidney transplant study (Cole et al., 1994, Transplantation 57, 60-67) are used for illustrative purposes.