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Testing a Claim about Standard Deviation01:19

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Using surrogate information to improve confirmatory platform trial with sample size re-estimation.

Chengxue Zhong1, Qing Li2, Liwen Wu3

  • 1Department of Biostatistics and Data Science, Biostatistics, University of Texas Health Science Center at Houston, Houston, Texas, USA.

Journal of Biopharmaceutical Statistics
|June 17, 2022
PubMed
Summary

Platform trials accelerate drug development by testing multiple treatments simultaneously. This study introduces a modified conditional power method using primary and surrogate endpoints for better interim decisions in these complex trials.

Keywords:
Adaptive designarm selectionmodified conditional powerplatform trialsample size re-estimationsurrogate endpoint

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacology

Background:

  • Platform trials enable simultaneous evaluation of multiple treatment arms against a common control, enhancing drug development efficiency.
  • Confirmatory platform trials face challenges with immature data during interim analyses, impacting treatment arm selection and sample size determination.
  • Accurate interim decision-making is crucial for the success and resource optimization of adaptive clinical trials.

Purpose of the Study:

  • To propose a novel methodology for interim analysis in confirmatory platform trials.
  • To address the challenge of utilizing immature data for treatment arm selection and sample size adjustments.
  • To enhance the efficiency and reliability of drug development through adaptive trial designs.

Main Methods:

  • Development of a modified conditional power (CP) approach for interim analyses.
  • Integration of data from both primary and surrogate endpoints into the modified CP calculation.
  • Application of the proposed method in a simulated case study for a lung cancer clinical trial.

Main Results:

  • The modified CP method provides a robust framework for making informed decisions at interim analyses.
  • Utilizing both primary and surrogate endpoints improves the accuracy of treatment arm selection and sample size determination.
  • The case study demonstrates the practical applicability and potential benefits of the proposed methodology.

Conclusions:

  • The modified conditional power approach offers a viable solution for handling immature data in confirmatory platform trials.
  • This methodology can lead to more efficient and reliable drug development by optimizing interim decision-making.
  • The findings support the broader adoption of advanced statistical methods in adaptive clinical trial designs.