Abstract
Recent developments proposed by Lin (1991) which allow for the sequential analysis of multivariate failure time data, are discussed in the context of clinical trials with marker process data. In particular, a marker based response observed as a univariate failure time variable is considered in a univariate manner and in combination with the primary failure time variable through global measures of treatment effect. A weighting scheme is introduced that is designed to make greater use of the marker process responses when they are consistent with the responses for the primary endpoint.
Univariate analyses and analyses based on global test statistics are evaluated with respect to duration of study and type I and type II error rates for a variety of relative risk parameter configurations. The simulation study is designed to extend the work of Machado, Gail and Ellenberg (1990) to sequential trials and to assess the performance of the global test statistics in this context. The global measures are found to be preferable over the univariate primary endpoint analyses when the treatment affects all transition intensities in a consistent manner. Further, there are advantages over the univariate marker based analysis when the treatment effects on some transition intensities are in opposite directions. Such a scenario remains problematic however with the relative error rates determined to a large extent by the baseline weighting scheme.