title: Exploring the relationship between the causal-inference and meta-analytic paradigms for the evaluation of surrogate endpoints.
abstract: Nowadays, two main frameworks for the evaluation of surrogate endpoints, based on causal-inference and meta-analysis, dominate the scene. Earlier work showed that the metrics of surrogacy introduced in both paradigms are related, although in a complex way that is difficult to study analytically. In the present work, this relationship is further examined using simulations and the analysis of a case study. The results indicate that the extent to which both paradigms lead to similar conclusions regarding the validity of the surrogate, depends on a complex interplay between multiple factors like the ratio of the between and within trial variability and the unidentifiable correlations between the potential outcomes. All the analyses were carried out using the newly developed R package Surrogate, which is freely available via CRAN.
authors.affiliation: I-BioStat, Universiteit Hasselt, B-3590, Diepenbeek, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Van der Elst
authors.affiliation: I-BioStat, Universiteit Hasselt, B-3590, Diepenbeek, Belgium.|I-BioStat, Katholieke Universiteit Leuven, B-3000, Leuven, Belgium.
authors.forename: Geert
authors.initials: G
authors.lastname: Molenberghs
authors.affiliation: I-BioStat, Katholieke Universiteit Leuven, B-3000, Leuven, Belgium.
authors.forename: Ariel
authors.initials: A
authors.lastname: Alonso
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D056808:Biostatistics; D015984:Causality; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D006801:Humans; D015201:Meta-Analysis as Topic; D015233:Models, Statistical
chemical_list: D015415:Biomarkers
keywords: R package surrogate; causal-inference approach; meta-analytic approach; surrogate markers