Considerations in the evaluation of surrogate endpoints in clinical trials: Summary of a National Institutes of Health Workshop

We report on recommendations from a National Institutes of Health Workshop on methods for evaluating the use of surrogate endpoints in clinical trials , which was attended by experts in biostatistics and clinical trials from a broad array of disease areas. Recent advances in biosciences and technolog y have increased the ability to understand, measure, and model biological m echanisms; appropriate application of these advances in clinical research s ettings requires collaboration of quantitative and laboratory scientists. B iomarkers, new examples of which arise rapidly from new technologies, are u sed frequently in such areas as early detection of disease and identificati on of patients most likely to benefit from new therapies. There is also sci entific interest in exploring whether, and under what conditions, biomarker s may substitute for clinical endpoints of phase III trials, although works hop participants agreed that these considerations apply primarily to situat ions where trials using clinical endpoints are not feasible. Evaluating can didate biomarkers in the exploratory phases of drug development and investi gating surrogate endpoints in confirmatory trials require the establishment of a statistical and inferential. framework. As a first step, participants reviewed methods for investigating the degree to which biomarkers can expl ain or predict the effect of treatments on clinical endpoints measured in c linical trials. They also suggested new approaches appropriate in settings where biomarkers reflect only indirectly the important processes on the cau sal path to clinical disease and where biomarker measurement errors are of concern. Participants emphasized the need for further research on developme nt of such models, whether they are empirical in nature or attempt to descr ibe mechanisms in mathematical terms. Of special interest were meta-analyti c models for combining information from multiple studies involving interven tions for the same condition. Recommendations also included considerations for design and conduct of trials and for assemblage of databases needed for such research. Finally, there was a strong recommendation for increased tr aining of quantitative scientists in biologic research as well as in statis tical methods and modeling to ensure that there will be an adequate workfor ce to meet future research needs. Control Clin Trials 2001; 22:485-502 (C) Elsevier Science Inc. 2001.