title: Statistical challenges in the evaluation of surrogate endpoints in randomized trials.
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.
authors.affiliation: Limburgs Universitair Centrum, tUL, Center for Statistics, Biostatistics, Diepenbeek, Belgium. geert.molenberghs@luc.ac.be
authors.forename: Geert
authors.initials: G
authors.lastname: Molenberghs
authors.forename: Marc
authors.initials: M
authors.lastname: Buyse
authors.forename: Helena
authors.initials: H
authors.lastname: Geys
authors.forename: Didier
authors.initials: D
authors.lastname: Renard
authors.forename: Tomasz
authors.initials: T
authors.lastname: Burzykowski
authors.forename: Ariel
authors.initials: A
authors.lastname: Alonso
mesh_terms: D023381:Endpoint Determination / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D015203:Reproducibility of Results