A predictive probability interim design for phase II clinical trials with continuous endpoints

Meng Liu1, Emily V Dressler2

  • 1Department of Biostatistics, University of Kentucky, Lexington, KY, U.S.A.

Insights

This study introduces a new statistical design for early-phase clinical trials of molecular targeted therapies. The proposed method efficiently monitors treatment futility and efficacy using continuous endpoints like tumor size.

Area of Science:

  • Clinical Trial Design
  • Biostatistics
  • Pharmacodynamics

Background:

  • Molecular targeted therapies offer improved safety profiles compared to traditional cytotoxic treatments.
  • Early phase trials increasingly focus on biological activity and target modulation.
  • Current interim analysis strategies are insufficient for continuous outcomes in single-arm phase II trials.

Purpose of the Study:

  • To develop and evaluate a novel two-stage adaptive trial design for molecular targeted therapies.
  • To accommodate continuous endpoints and enable interim monitoring for futility and efficacy.
  • To optimize resource allocation and decision-making in early phase drug development.

Main Methods:

  • A two-stage adaptive design based on predictive probability was proposed.
  • The design assumes continuous endpoints (e.g., tumor size) with a normal distribution and known variance.
  • Simulations and a case study were used to assess the design's performance.

Main Results:

  • The proposed design effectively allows for interim stopping due to futility or efficacy.
  • Using continuous tumor size as an endpoint reduced required sample sizes.
  • The design demonstrated robustness across various prior assumptions.

Conclusions:

  • The developed statistical design provides a flexible and efficient framework for early-phase trials of molecular targeted therapies.
  • This approach supports adaptive decision-making by incorporating interim analyses for continuous outcomes.
  • The methodology facilitates prioritizing promising targeted therapies based on robust early-phase data.

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