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Selection of composite binary endpoints in clinical trials.

Marta Bofill Roig1, Guadalupe Gómez Melis1

  • 1Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, 08034, Barcelona, Spain.

Biometrical Journal. Biometrische Zeitschrift
|October 13, 2017
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Summary

Choosing a primary endpoint for clinical trials is crucial. This study extends the ARE method for binary endpoints, offering guidelines to select the most effective primary endpoint based on key parameters.

Keywords:
asymptotic relative efficiencybinary endpointclinical trialcomposite endpointtreatment effects

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Area of Science:

  • Clinical Trials Methodology
  • Biostatistics
  • Medical Research Design

Background:

  • Composite endpoints increase event counts and trial power but can complicate interpretation.
  • The Gómez and Lagakos ARE method aids in selecting primary endpoints for time-to-event data.
  • Challenges exist in applying composite endpoints when components lack clinical similarity or have differing treatment effects.

Purpose of the Study:

  • To extend the Asymptotic Relative Efficiency (ARE) method for primary endpoint selection to binary outcomes.
  • To provide a framework for choosing between composite and component endpoints in clinical trials with binary data.
  • To analyze the impact of various parameters on the optimal choice of a primary endpoint.

Main Methods:

  • Adaptation of the Gómez and Lagakos ARE method for binary endpoints.
  • Identification and analysis of six key parameters influencing endpoint selection: association, event proportion, and odds ratios.
  • Application of a case study to demonstrate the extended ARE methodology.

Main Results:

  • The extended ARE method for binary endpoints is dependent on six specific parameters.
  • Parameter values, including event proportion and treatment effect (odds ratio), significantly influence the optimal endpoint choice.
  • The methodology provides a quantitative approach to compare composite versus single binary endpoints.

Conclusions:

  • The expanded ARE method offers a robust approach for selecting primary endpoints in binary outcome clinical trials.
  • Guidelines are provided for researchers to determine the most suitable primary endpoint based on anticipated trial parameters.
  • This work enhances the statistical rigor in clinical trial design, particularly for binary endpoints.