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Multiplicity Control in Oncology Clinical Trials With a Binary Surrogate Endpoint-Based Drop-The-Losers Design.

Weibin Zhong1, Jing-Ou Liu1, Chenguang Wang1

  • 1Biostatistics and Data Management, Regeneron Pharmaceuticals, Tarrytown, New York, USA.

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|September 5, 2025
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Summary

Adaptive phase 2/3 seamless designs improve oncology dose selection by evaluating multiple doses. The "drop-the-losers" approach identifies effective treatments early, optimizing clinical trials for targeted agents and immunotherapies.

Keywords:
dose selectiondrop‐the‐losers designmultiplicity controlsurrogate endpoint

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Area of Science:

  • Clinical Trials Methodology
  • Oncology Drug Development
  • Biostatistics

Background:

  • Traditional phase 1 oncology studies often select a single maximum tolerated dose for later phases.
  • The rise of targeted agents and immunotherapies necessitates evaluating multiple doses for optimal selection.
  • Phase 2 randomized studies are commonly used for this dose evaluation, but adaptive designs offer potential efficiencies.

Purpose of the Study:

  • To evaluate the adaptive phase 2/3 seamless design for dose selection in oncology.
  • To assess the "drop-the-losers" strategy within this adaptive framework.
  • To analyze type I error inflation and influencing factors in such designs.

Main Methods:

  • Application of an adaptive phase 2/3 seamless design, specifically the "drop-the-losers" approach.
  • Utilizing a binary surrogate endpoint (e.g., overall response) for early arm selection.
  • Theoretical derivation of type I error inflation scale and simulation studies to assess design performance.
  • Demonstration with a lung cancer trial example and introduction of implementation software.

Main Results:

  • Quantification of theoretical type I error inflation scale for the adaptive design.
  • Simulation studies illustrating the impact of various factors on type I error inflation.
  • Practical application demonstrated through a lung cancer trial design.

Conclusions:

  • Adaptive phase 2/3 seamless designs, particularly the "drop-the-losers" method, offer a structured approach to dose selection in oncology.
  • Understanding and quantifying type I error inflation is crucial for robust implementation.
  • The proposed design and associated software facilitate efficient and effective dose selection for novel cancer therapies.