ABSTRACT
A surrogate endpoint is a biomarker, intended for substituting a clinical endpoint. Surrogate endpoints can play a role in the earlier detection of safety signals that could point to toxicity problems with new drugs. This chapter gives a perspective on data from a single trial. It presents the meta-analytic evaluation framework in the context of normally distributed outcomes. M. Buyse and G. Molenberghs proposed quantity for the validation of a surrogate endpoint: the relative effect, which is the ratio of the effects of treatment upon the true and the surrogate endpoint. A variety of surrogate marker evaluation strategies have been proposed, cast within a meta-analytic framework. The meta-analytic approach was formulated originally for two continuous, normally distributed outcomes, and extended in the meantime to various outcome types, ranging from continuous, binary, ordinal, time-to-event, and longitudinally measured outcomes. The chapter discusses the settings of binary endpoints, failure-time endpoints, the combination of an ordinal and a survival endpoint, and longitudinal endpoints.
