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Optimal futility stopping boundaries for binary endpoints.

Michaela Maria Freitag1, Xieran Li2,3, Geraldine Rauch2,4,5

  • 1Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, 10117, Berlin, Germany. michaela-maria.freitag@charite.de.

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Summary
This summary is machine-generated.

Optimized futility boundaries in phase II clinical trials improve decision-making by minimizing wrong futility stops. This new method offers a flexible alternative to Simon's designs, enhancing study efficiency.

Keywords:
Binary endpointFutility stopGroup sequential designSingle-arm phase II trial

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Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Pharmaceutical Research

Background:

  • Group sequential designs with futility stopping conserve resources in clinical trials.
  • Simon's designs are common for binary endpoints in single-arm phase II studies but have limitations regarding false futility declarations and sample size efficiency.
  • Optimizing futility boundaries is crucial for study performance, impacting power and accuracy of stopping decisions.

Purpose of the Study:

  • To extend optimality criteria for futility boundaries to binary endpoints in single-arm phase II studies.
  • To introduce an algorithm for deriving optimized futility boundaries.
  • To compare the performance of these optimized boundaries against established Simon's designs and their modifications.

Main Methods:

  • Developed an algorithm to derive optimized futility boundaries based on criteria by Schüler et al.
  • Extended the approach to binary endpoints for single-arm phase II studies.
  • Compared operating characteristics (e.g., sample size, power, futility error rates) with Simon's optimal and minimax designs and Kim et al.'s modified designs.

Main Results:

  • Optimized futility boundaries maximize correct futility stopping while constraining power loss and wrong futility stops.
  • Operating characteristics, including maximum and expected sample sizes, are comparable or superior to Simon's designs.
  • Proposed boundaries are non-binding, offering flexibility compared to Simon's binding rules.

Conclusions:

  • Futility boundary selection and interim analysis timing significantly impact study design performance.
  • The proposed method offers a flexible, non-binding alternative to Simon's designs for phase II studies.
  • Optimized futility boundaries minimize the probability of wrongly stopping for futility and avoid common drawbacks of Simon's designs.