In many therapeutic areas, the identification and validation of surrogate endpoints is of prime interest to reduce the duration and/or size of clinical trials. Buyse et al. [Biostatistics 2000; 1:49–67] proposed a meta-analytic approach to the validation. In this approach, the validity of a surrogate is quantified by the coefficient of determination R obtained from a model, which allows for prediction of the treatment effect on the endpoint of interest (‘true’ endpoint) from the effect on the surrogate. One problem related to the use of R is the difficulty in interpreting its value. To address this difficulty, in this paper we introduce a new concept, the so-called surrogate threshold effect (STE), defined as the minimum treatment effect on the surrogate necessary to predict a non-zero effect on the true endpoint. One of its interesting features, apart from providing information relevant to the practical use of a surrogate endpoint, is its natural interpretation from a clinical point of view. Copyright © 2006 John Wiley & Sons, Ltd.