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Updated: Jan 19, 2026

The Mantel-Cox Log-Rank Test
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Flexibly Monitoring Group Sequential Survival Trials When Testing is Based Upon a Weighted Log-Rank Statistic.

Sean S Brummel1, Daniel L Gillen2

  • 1Harvard School of Public Health, Center for Biostatistics in AIDS Research, Boston, Massachusetts, USA.

Sequential Analysis
|September 11, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a constrained boundaries method for repeated group sequential testing with time-varying treatment effects. This approach ensures reliable monitoring of weighted logrank statistics, even with non-linear information growth.

Keywords:
62L0562L1062N03Constrained boundariesGroup sequentialInformationMonitoringNonparametricNonproportional hazardsSurvivalWeighted logrank

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Survival Analysis

Background:

  • Group sequential methods are crucial for adaptive clinical trial monitoring.
  • Time-varying treatment effects and non-linear information growth complicate interim analyses.
  • Weighted logrank statistics are commonly used for survival endpoints.

Purpose of the Study:

  • To propose and evaluate a constrained boundaries approach for group sequential testing.
  • To address the challenges of monitoring weighted logrank statistics with non-linear information growth.
  • To maintain the operating characteristics of group sequential designs under these conditions.

Main Methods:

  • Development of a constrained boundaries method for group sequential designs.
  • Application to weighted logrank statistics for survival endpoints.
  • Simulation studies to assess operating characteristics.
  • Case study for practical illustration.

Main Results:

  • The constrained boundaries approach effectively maintains planned operating characteristics.
  • Accurate estimation of entry and survival distributions is necessary at interim analyses.
  • The proposed method demonstrates feasibility and utility in a case study.

Conclusions:

  • Constrained boundaries offer a robust solution for monitoring group sequential trials with time-varying effects.
  • Interim estimation of patient entry and survival is vital for accurate monitoring.
  • This methodology enhances the reliability of adaptive clinical trial designs.