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Time-to-event surrogate endpoint validation using mediation analysis and meta-analytic data.

Quentin Le Coënt1, Catherine Legrand2, Virginie Rondeau1

  • 1Department of Biostatistics, Bordeaux Population Health Research Center, INSERM U1219, 146 rue Léo Saignat, 33076 Bordeaux, France.

Biostatistics (Oxford, England)
|November 18, 2022
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Summary

This study introduces a new statistical method to validate surrogate endpoints in oncology clinical trials. The approach uses mediation analysis on meta-analytic data to measure how effectively a surrogate predicts the final outcome, improving trial feasibility.

Keywords:
Joint modelingMediation analysisMeta-analysisSurrogacyTime-to-event

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Oncology Research

Background:

  • Increasing survival in oncology necessitates longer follow-up for overall survival endpoints, potentially compromising clinical trial feasibility.
  • Surrogate endpoints offer a potential solution but require rigorous statistical validation before adoption in clinical trials.

Approach:

  • Proposes a novel statistical approach for validating surrogate endpoints when both surrogate and final endpoints are censored event times.
  • Employs mediation analysis within a joint model framework to quantify the indirect effect of treatment through the surrogate endpoint.
  • Accounts for meta-analytic data and trial-level random effects to provide a robust measure of surrogacy.

Key Points:

  • The method decomposes the total treatment effect into direct and indirect effects, with the indirect effect mediated by the surrogate.
  • A proportion of the indirect effect to the total effect serves as a quantitative measure of surrogacy.
  • Successfully applied to assess time-to-relapse as a surrogate for overall survival in resectable gastric cancer.

Conclusions:

  • The proposed meta-analytic mediation approach provides a statistically sound method for surrogate endpoint validation.
  • This methodology can enhance the efficiency and feasibility of oncology clinical trials by enabling the use of validated surrogate endpoints.