Surrogacy marker paradox measures in meta-analytic settings.

ABSTRACT: Because of the time and expense required to obtain clinical outcomes of interest, such as functional limitations or death, clinical trials often focus the effects of treatment on earlier and more easily obtained surrogate markers. Preliminary work to define surrogates focused on the fraction of a treatment effect "explained" by a marker in a regression model, but as notions of causality have been formalized in the statistical setting, formal definitions of high-quality surrogate markers have been developed in the causal inference framework, using either the "causal effect" or "causal association" settings. In the causal effect setting, high-quality surrogate markers have a large fraction of the total treatment effect explained by the effect of the treatment on the marker net of the treatme

SUBMITTER: Elliott MR 

PROVIDER: S-EPMC4366594 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature