Statistical challenges in the evaluation of surrogate endpoints in randomized trials

Control Clin Trials. 2002 Dec;23(6):607-25. doi: 10.1016/s0197-2456(02)00236-2.

Abstract

The validation of surrogate endpoints has been studied by Prentice, who presented a definition as well as a set of criteria that are equivalent if the surrogate and true endpoints are binary. Freedman et al. supplemented these criteria with the so-called proportion explained. Buyse and Molenberghs proposed to replace the proportion explained by two quantities: (1). the relative effect, linking the effect of treatment on both endpoints, and (2). the adjusted association, an individual-level measure of agreement between both endpoints. In a multiunit setting, these quantities can be generalized to a trial-level measure of surrogacy and an individual-level measure of surrogacy. In this paper, we argue that such a multiunit approach should be adopted because it overcomes difficulties that necessarily surround validation efforts based on a single trial. These difficulties are highlighted.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Endpoint Determination / statistics & numerical data*
  • Humans
  • Models, Statistical
  • Randomized Controlled Trials as Topic / statistics & numerical data*
  • Reproducibility of Results