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Smoothing Corrections for Improving Sample Size Recalculation Rules in Adaptive Group Sequential Study Designs.

Carolin Herrmann1, Geraldine Rauch1

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Adaptive group sequential designs allow for sample size recalculation during clinical trials. Smoothing sample size recalculation rules reduces variability and improves trial performance, offering a practical tool for better study planning.

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Area of Science:

  • Clinical trial design
  • Biostatistics
  • Adaptive study designs

Background:

  • Adequate sample size calculation is crucial for clinical trial success.
  • Adaptive group sequential designs permit sample size adjustments during a trial.
  • Interim effect testing determines if a trial continues or stops, with potential for sample size recalculation.

Purpose of the Study:

  • To address limitations of existing sample size recalculation rules, specifically high variability.
  • To develop a tool to improve the performance of sample size recalculation.
  • To investigate smoother sample size recalculation functions to reduce variability.

Main Methods:

  • Interpreting sample size recalculation rules as functions of the interim effect.
  • Investigating smoother increases in sample size recalculation functions to mitigate variability.
  • Evaluating design options using Monte Carlo simulations with criteria like conditional power and a combined performance score.

Main Results:

  • Smoothing corrections effectively reduce variability in conditional power and sample size.
  • Smoother recalculation functions enhance trial performance, particularly for medium and large effect sizes.
  • The proposed approach demonstrates improved performance based on a conditional performance score.

Conclusions:

  • A practical tool is presented to improve sample size recalculation rules, based on simulation findings.
  • The proposed smoothing approach is easily implemented and can complement existing methods.
  • This tool enhances the reliability and efficiency of adaptive clinical trial designs.