Tests and confidence intervals for secondary endpoints in sequential clinical trials

In a sequential clinical trial whose stopping rule depends on the primary endpoint, inference on secondary endpoints is an important long-standing problem. Ignoring the possibility of early stopping based on the primary endpoint may result in substantial bias. To address this problem, a commonly used approach is to develop bias correction by estimating the bias in the case of bivariate normal outcomes and appealing to joint asymptotic normality of the statistics associated with the primary and secondary endpoints. We propose herein a new approach that uses resampling and a novel ordering scheme in the sample space of sequential statistics observed up to a stopping time. This approach is shown to provide accurate inference in complex clinical trials, including time-sequential trials with survival endpoints and covariates. Copyright 2009, Oxford University Press.