Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.

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

Original Publication: Chichester ; New York : Wiley, c1982-

Biomarkers* ; Causality* ; Normal Distribution*; Data Interpretation, Statistical ; Humans ; Models, Statistical ; Randomized Controlled Trials as Topic/methods

Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities.
(Copyright © 2017 John Wiley & Sons, Ltd.)

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MR/L011964/1 United Kingdom MRC_ Medical Research Council; R01 CA129102 United States CA NCI NIH HHS; T32 CA083654 United States CA NCI NIH HHS

Keywords: causal association; direct effects; principal stratification; surrogate markers; unmeasured confounders

0 (Biomarkers)

Date Created: 20170809 Date Completed: 20180625 Latest Revision: 20220129

20221213

PMC5675829

10.1002/sim.7430

28786131