4.2 Article

Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes

Journal

LIFETIME DATA ANALYSIS
Volume 26, Issue 2, Pages 266-291

Publisher

SPRINGER
DOI: 10.1007/s10985-019-09470-4

Keywords

Bivariate dependence; Error-spending method; Independent censoring; Logrank statistic; Non-fatal events; Normal approximation

Funding

  1. JSPS KAKENHI [JP17K00054, JP17K00069]
  2. Japan Agency for Medical Research and Development (AMED) [18lk0201061h0002/18lk0201061h0202]
  3. National Institute of Allergy and Infectious Diseases of the National Institutes of Health [UM1AI068634]

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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.

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