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DOD-SSR: An Adaptive Seamless Phase II/III Design With Dose Optimization Decision and Sample Size Re-estimation.

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Summary
This summary is machine-generated.

This study introduces a novel seamless Phase II/III trial design using Bayesian predictive probability of success (PPoS) for selecting optimal treatment arms and re-estimating sample size (SSR) with surrogate endpoints, accelerating drug development.

Keywords:
Bayesian predictive probability of successadaptive designmultiplicitysurrogate endpointstype I error

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Drug Development

Background:

  • Seamless Phase II/III designs accelerate drug development by integrating exploratory and confirmatory phases.
  • Dose optimization and early decision-making are critical in modern clinical trials.
  • Fixed sample sizes in early-phase trials pose challenges due to limited data and high risks.

Purpose of the Study:

  • To introduce a novel seamless Phase II/III design for multiple treatment arms.
  • To leverage Bayesian predictive probability of success (PPoS) for treatment arm selection and interim sample size re-estimation (SSR).
  • To utilize surrogate endpoints for making informed interim decisions.

Main Methods:

  • A Bayesian framework incorporating PPoS for treatment arm selection and SSR.
  • Integration of surrogate endpoints for interim analyses.
  • Comparison with traditional separate Phase II/III designs and alternative seamless designs.

Main Results:

  • The proposed design enhances the likelihood of selecting favorable treatment arms.
  • Improved overall statistical power and reduced average trial size and duration.
  • Demonstrated superior performance compared to existing seamless designs without SSR or using conditional power.

Conclusions:

  • The novel seamless Phase II/III design offers significant advantages in efficiency and success probability.
  • The framework effectively utilizes PPoS and surrogate endpoints for adaptive decision-making.
  • Applicable to various therapeutic areas, including non-small cell lung cancer (NSCLC).