Quantifying proportion of treatment effect by surrogate endpoint under heterogeneity.

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  • Additional Information
    • Source:
      Publisher: SAGE Publications Country of Publication: England NLM ID: 9212457 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1477-0334 (Electronic) Linking ISSN: 09622802 NLM ISO Abbreviation: Stat Methods Med Res Subsets: MEDLINE
    • Publication Information:
      Publication: London : SAGE Publications
      Original Publication: Sevenoaks, Kent, UK : Edward Arnold, c1992-
    • Subject Terms:
      Biomarkers* ; Randomized Controlled Trials as Topic*/statistics & numerical data ; Models, Statistical* ; Infliximab*/therapeutic use; Humans ; Endpoint Determination/statistics & numerical data ; Treatment Outcome ; Statistics, Nonparametric ; Computer Simulation
    • Abstract:
      When the primary endpoints in randomized clinical trials require long term follow-up or are costly to measure, it is often desirable to assess treatment effects on surrogate instead of clinical endpoints. Prior to adopting a surrogate endpoint for such purposes, the extent of its surrogacy on the primary endpoint must be assessed. There is a rich statistical literature on assessing surrogacy in the overall population, much of which is based on quantifying the proportion of treatment effect on the primary endpoint that is explained by the treatment effect on the surrogate endpoint. However, the surrogacy of an endpoint may vary across different patient subgroups according to baseline demographic characteristics, and limited methods are currently available to assess overall surrogacy in the presence of potential surrogacy heterogeneity. In this paper, we propose methods that incorporate covariates for baseline information, such as age, to improve overall surrogacy assessment. We use flexible semi-non-parametric modeling strategies to adjust for covariate effects and derive a robust estimate for the proportion of treatment effect of the covariate-adjusted surrogate endpoint. Simulation results suggest that the adjusted surrogate endpoint has greater proportion of treatment effect compared to the unadjusted surrogate endpoint. We apply the proposed method to data from a clinical trial of infliximab and assess the adequacy of the surrogate endpoint in the presence of age heterogeneity.
      Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
    • Contributed Indexing:
      Keywords: Covariate-adjusted; heterogeneity; proportion of treatment effect explained; randomized clinical trials; surrogacy
    • Accession Number:
      0 (Biomarkers)
      B72HH48FLU (Infliximab)
    • Publication Date:
      Date Created: 20240508 Date Completed: 20240826 Latest Revision: 20240826
    • Publication Date:
      20240826
    • Accession Number:
      10.1177/09622802241247719
    • Accession Number:
      38717356