The meta-analytic framework for the evaluation of surrogate endpoints in clinical trials

For a number of reasons, surrogate endpoints are considered instead of the so-called true endpoint in clinical studies, especially when such endpoints can be measured earlier, and/or with less burden for patient and experimenter. Surrogate endpoints may occur more frequently than their standard counterparts. For these reasons, it is not surprising that the use of surrogate endpoints in clinical practice is increasing.Building on the seminal work of Prentice [1989. Surrogate endpoints in clinical trials: definitions and operational criteria. Statist. Med. 8, 431–440] and Freedman et al. [1992. Statistical validation of intermediate endpoints for chronic diseases. Statist. Med. 11, 167–178], Buyse et al. [2000. The validation of surrogate endpoints in meta-analyses of randomized experiments. Biostatistics 1, 49–67] framed the evaluation exercise within a meta-analytic setting, in an effort to overcome difficulties that necessarily surround evaluation efforts based on a single trial. In this paper, we review the meta-analytic approach for continuous outcomes, discuss extensions to non-normal and longitudinal settings, as well as proposals to unify the somewhat disparate collection of validation measures currently on the market. Implications for design and for predicting the effect of treatment in a new trial, based on the surrogate, are discussed. Two case studies are analyzed, one in schizophrenia and one in opthalmology.