Open AccessGroup-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes
Author(s) -
Tomoyuki Sugimoto,
Toshimitsu Hamasaki,
Scott Evans,
Susan Halabi
Publication year - 2019
Publication title -
lifetime data analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.677
H-Index - 46
eISSN - 1572-9249
pISSN - 1380-7870
DOI - 10.1007/s10985-019-09470-4
Subject(s) - statistics , bivariate analysis , mathematics , event (particle physics) , random variate , statistic , log rank test , sample size determination , joint probability distribution , survival analysis , random variable , physics , quantum mechanics
We discuss the multivariate (2L-variate) correlation structure and the asymptotic distribution for the group-sequential weighted logrank statistics formulated when monitoring two correlated event-time outcomes in clinical trials. The asymptotic distribution and the variance-covariance for the 2L-variate weighted logrank statistic are derived as available in various group-sequential trial designs. These methods are used to determine a group-sequential testing procedure based on calendar times or information fractions. We apply the theoretical results to a group-sequential method for monitoring a clinical trial with early stopping for efficacy when the trial is designed to evaluate the joint effect on two correlated event-time outcomes. We illustrate the method with application to a clinical trial and describe how to calculate the required sample sizes and numbers of events.