Studentized permutation method for comparing two restricted mean survival times with small sample from randomized trials

Author:

Ditzhaus Marc12ORCID,Yu Menggang3,Xu Jin4ORCID

Affiliation:

1. Department of Statistics TU Dortmund University Dortmund Germany

2. Department of Mathematics Otto‐von‐Guericke University Magdeburg Germany

3. Department of Biostatistics and Medical Informatics University of Wisconsin Madison Wisconsin USA

4. Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE and School of Statistics East China Normal University Shanghai China

Abstract

Recent observations, especially in cancer immunotherapy clinical trials with time‐to‐event outcomes, show that the commonly used proportional hazard assumption is often not justifiable, hampering an appropriate analysis of the data by hazard ratios. An attractive alternative advocated is given by the restricted mean survival time (RMST), which does not rely on any model assumption and can always be interpreted intuitively. Since methods for the RMST based on asymptotic theory suffer from inflated type‐I error under small sample sizes, a permutation test was proposed recently leading to more convincing results in simulations. However, classical permutation strategies require an exchangeable data setup between comparison groups which may be limiting in practice. Besides, it is not possible to invert related testing procedures to obtain valid confidence intervals, which can provide more in‐depth information. In this paper, we address these limitations by proposing a studentized permutation test as well as respective permutation‐based confidence intervals. In an extensive simulation study, we demonstrate the advantage of our new method, especially in situations with relatively small sample sizes and unbalanced groups. Finally, we illustrate the application of the proposed method by re‐analyzing data from a recent lung cancer clinical trial.

Funder

Deutsche Forschungsgemeinschaft

National Cancer Institute

National Institute of Dental and Craniofacial Research

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

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