On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints

A. Alonso, W. van der Elst, G. Molenberghs, M. Buyse, T. Burzykowski

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The increasing cost of drug development has raised the demand for surrogate endpoints when evaluating new drugs in clinical trials. However, over the years, it has become clear that surrogate endpoints need to be statistically evaluated and deemed valid, before they can be used as substitutes of true endpoints in clinical studies. Nowadays, two paradigms, based on causal-inference and meta-analysis, dominate the scene. Nonetheless, although the literature emanating from these paradigms is wide, till now the relationship between them has largely been left unexplored. In the present work, we discuss the conceptual framework underlying both approaches and study the relationship between them using theoretical elements and the analysis of a real case study. Furthermore, we show that the meta-analytic approach can be embedded within a causal-inference framework on the one hand and that it can be heuristically justified why surrogate endpoints successfully evaluated using this approach will often be appealing from a causal-inference perspective as well, on the other. A newly developed and user friendly R package Surrogate is provided to carry out the evaluation exercise.

Original languageEnglish
Pages (from-to)15-24
Number of pages10
JournalBiometrics
Volume71
Issue number1
Early online date1 Oct 2014
DOIs
Publication statusPublished - Mar 2015

Keywords

  • Causal-inference
  • Meta-analytic approach
  • Surrogate endpoints
  • CRITERIA
  • MODELS

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