Exploring the relationship between the causal-inference and meta-analytic paradigms for the evaluation of surrogate endpoints.

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  • Additional Information
    • Source:
      Publisher: Wiley Country of Publication: England NLM ID: 8215016 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1097-0258 (Electronic) Linking ISSN: 02776715 NLM ISO Abbreviation: Stat Med Subsets: MEDLINE
    • Publication Information:
      Original Publication: Chichester ; New York : Wiley, c1982-
    • Subject Terms:
      Biomarkers/*analysis ; Clinical Trials as Topic/*statistics & numerical data ; Endpoint Determination/*statistics & numerical data; Biostatistics ; Causality ; Computer Simulation ; Humans ; Meta-Analysis as Topic ; Models, Statistical
    • 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.
      (Copyright © 2015 John Wiley & Sons, Ltd.)
    • Contributed Indexing:
      Keywords: R package surrogate; causal-inference approach; meta-analytic approach; surrogate markers
    • Accession Number:
      0 (Biomarkers)
    • Publication Date:
      Date Created: 20151128 Date Completed: 20161227 Latest Revision: 20161230
    • Publication Date:
      20221213
    • Accession Number:
      10.1002/sim.6807
    • Accession Number:
      26612787