Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition

Gilbert Peter B. (), Gabriel Erin E. (), Huang Ying () and Chan Ivan S.F. ()
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Gilbert Peter B.: Vaccine Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
Gabriel Erin E.: Biostatistics Branch, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20817, USA
Huang Ying: Vaccine Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Department of Biostatistics, University of Washington, Seattle, WA 98105, USA
Chan Ivan S.F.: Merck & Co., Whitehouse Station, NJ 08889, USA

Journal of Causal Inference, 2015, vol. 3, issue 2, 157-175

Abstract: A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a way to make correct inferences on clinical treatment effects in future studies without needing to collect the clinical endpoint data. Within the principal stratification framework for addressing this problem based on data from a single randomized clinical efficacy trial, a variety of definitions and criteria for a good surrogate endpoint have been proposed, all based on or closely related to the “principal effects” or “causal effect predictiveness (CEP)” surface. We discuss CEP-based criteria for a useful surrogate endpoint, including (1) the meaning and relative importance of proposed criteria including average causal necessity (ACN), average causal sufficiency (ACS), and large clinical effect modification; (2) the relationship between these criteria and the Prentice definition of a valid surrogate endpoint; and (3) the relationship between these criteria and the consistency criterion (i.e. assurance against the “surrogate paradox”). This includes the result that ACN plus a strong version of ACS generally do not imply the Prentice definition nor the consistency criterion, but they do have these implications in special cases. Moreover, the converse does not hold except in a special case with a binary candidate surrogate. The results highlight that assumptions about the treatment effect on the clinical endpoint before the candidate surrogate is measured are influential for the ability to draw conclusions about the Prentice definition or consistency. In addition, we emphasize that in some scenarios that occur commonly in practice, the principal strata subpopulations for inference are identifiable from the observable data, in which cases the principal stratification framework has relatively high utility for the purpose of effect modification analysis and is closely connected to the treatment marker selection problem. The results are illustrated with application to a vaccine efficacy trial, where ACN and ACS for an antibody marker are found to be consistent with the data and hence support the Prentice definition and consistency.

Keywords: clinical trial; principal stratification; surrogate paradox; vaccine efficacy trial; Zoster (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:3:y:2015:i:2:p:157-175:n:2

DOI: 10.1515/jci-2014-0007

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