A perspective on surrogate endpoints in controlled clinical trials

TLDR

Surrogate endpoint validation has evolved over the past two decades, beginning with Prentice’s single‑trial framework and expanding to hierarchical, meta‑analytic approaches that integrate multiple trials. This paper reviews the single‑trial and hierarchical surrogate‑endpoint frameworks and discusses the statistical challenges of validating surrogate endpoints. The authors synthesize scattered applications and identify key statistical issues involved in surrogate‑endpoint validation.

Abstract

The last couple of decades have seen a large amount of activity in the area of surrogate marker and surrogate endpoint validation, both from a clinical and a statistical perspective. Prentice 1 made a pivotal contribution in the context of a single trial. Subsequently, the framework he proposed has been discussed, criticized, and extended. An important class of extensions considers several rather than a single trial. Recently, a lot of work has been done in this so-called hierarchical or meta-analytic framework. In this paper, we review both the single trial and the hierarchical framework. A number of applications, scattered throughout the literature, are brought together. We outline the statistical issues involved in trying to validate surrogate endpoints. Clearly statistical evidence should only be seen as a component in a decision making process that also involves a number of clinical and biological considerations.