Optimal two-stage designs for exploratory basket trials

Heng Zhou1, Fang Liu1, Cai Wu1

  • 1Biostatistics and Research Decision Sciences, Merck & Co., Inc, Kenilworth, NJ 07033, USA.

Insights

This study introduces novel two-stage basket trial designs for exploratory oncology clinical trials. These designs efficiently identify effective drugs by pruning inactive tumor indications and pooling active ones, controlling error rates effectively.

Area of Science:

  • Oncology
  • Clinical Trial Design
  • Biostatistics

Background:

  • Exploratory oncology trials aim to identify effective drugs for further development.
  • Basket trials test a single drug across multiple tumor indications to mitigate selection errors.
  • Existing designs may not optimally balance efficiency and statistical rigor in multi-indication settings.

Purpose of the Study:

  • To propose optimal and minimax two-stage basket trial designs for exploratory oncology studies.
  • To provide methods that explicitly control type I and type II error rates.
  • To offer a framework extending single-arm trial designs to multi-arm basket trials.

Main Methods:

  • Development of optimal and minimax two-stage basket trial designs.
  • Incorporation of a stage 1 to prune inactive tumor indications.
  • Stage 2 involves pooling active indications for overall drug effectiveness assessment.
  • Derivation of closed-form sample size formulas.
  • Simulation studies to compare performance against existing methods.

Main Results:

  • The proposed designs effectively prune inactive tumor indications early in the trial.
  • Active indications are pooled in stage 2 for robust effectiveness evaluation.
  • The designs offer explicit control over type I and type II error rates.
  • Simulation results demonstrate favorable operating characteristics compared to alternative methods.

Conclusions:

  • The proposed two-stage basket trial designs provide an efficient and statistically sound approach for exploratory oncology.
  • These designs represent a valuable extension of established single-arm trial methodologies to multi-arm settings.
  • The methods facilitate better drug candidate selection in early-phase oncology research.

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