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Group sequential designs with robust semiparametric recurrent event models.

Tobias Mütze1, Ekkehard Glimm2,3, Heinz Schmidli2

  • 11 Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.

Statistical Methods in Medical Research
|June 13, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces two group sequential procedures for analyzing recurrent events in clinical trials, offering flexible methods for chronic heart failure research. Both methods showed similar performance, with one providing better type I error control in certain scenarios.

Keywords:
Andersen–GillGroup sequentialheart failureinterim analysisrecurrent eventsrobust analysis

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Epidemiology

Background:

  • Robust semiparametric models are increasingly used for recurrent event analysis in clinical trials, offering flexibility over parametric models.
  • Implementing group sequential designs with these models is challenging due to the asymptotic distribution of Wald statistics.
  • This is particularly relevant for chronic heart failure trials, such as the PARAGON-HF trial.

Purpose of the Study:

  • To propose and evaluate two group sequential procedures for robust semiparametric analysis of recurrent events.
  • To provide methods for determining maximum information for planning clinical trials using these procedures.
  • To compare the operating characteristics of the proposed procedures.

Main Methods:

  • Developed two group sequential procedures: one based on asymptotic covariance of Wald statistics (guarantees Type I error control) and another on the canonical joint distribution (easier implementation).
  • Described a method for calculating maximum information for trial planning.
  • Conducted a simulation study motivated by the PARAGON-HF trial.

Main Results:

  • Both proposed group sequential procedures demonstrated similar operating characteristics.
  • The procedure based on the canonical joint distribution showed advantages in controlling the Type I error rate in specific scenarios.
  • The proposed method for maximum information calculation ensures appropriately powered trials for both procedures.

Conclusions:

  • The proposed group sequential procedures offer viable options for robust semiparametric analysis of recurrent events in clinical trials.
  • The choice between procedures may depend on the specific trial context, balancing Type I error control and implementation ease.
  • The developed methods support robust trial planning and analysis for recurrent event data.