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Statistical considerations when using a composite endpoint for comparing treatment groups

Authors

  • Guadalupe Gómez,

    Corresponding author
    1. Universitat Politècnica de Catalunya, Barcelona, Spain
    • Correspondence to: Guadalupe Gómez, Departament d'Estadística i I.O., Universitat Politècnica de Catalunya, Barcelona, Spain.

      E-mail: lupe.gomez@upc.edu

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  • Stephen W. Lagakos

    1. Department of Biostatistics, Harvard School of Public Health
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    • This research started as a joint effort by both authors. Unfortunately, the untimely death of Professor Lagakos did not allow him to contribute to the writing of the manuscript.


Abstract

When comparing two treatment groups in a time-to-event analysis, it is common to use a composite event consisting of two or more distinct outcomes. The goal of this paper is to develop a statistical methodology to derive efficiency guidelines for deciding whether to expand a study primary endpoint from inline image (for example, non-fatal myocardial infarction and cardiovascular death) to the composite of inline image and inline image (for example, non-fatal myocardial infarction, cardiovascular death or revascularisation). We investigate this problem by considering the asymptotic relative efficiency of a log-rank test for comparing treatment groups with respect to a primary relevant endpoint inline image versus the composite primary endpoint, say inline image, of inline image and inline image, where inline image is some additional endpoint. Copyright © 2012 John Wiley & Sons, Ltd.

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