The Statistical Evaluation of Surrogate Endpoints in Clinical Trials Virtual event
Both humanitarian and commercial considerations have spurred intensive search for methods to reduce the time and cost required to develop new therapies. The identification and use of surrogate endpoints, i.e. measures that can replace or supplement other endpoints in evaluations of experimental treatments or interventions, is a general strategy that has stimulated much enthusiasm. Surrogate endpoints are useful when they can be measured earlier, more conveniently, or more frequently than the “true” endpoints of primary interest. Regulatory agencies around the globe, particularly in the United States, Europe, and Japan, are introducing provisions and policies relating to the use of surrogate endpoints in registration studies. But how can one establish the adequacy of a surrogate, in the sense that treatment effectiveness on the surrogate will accurately predict treatment effect on the intended, and more important, true outcome? What kind of evidence is needed, and what statistical methods portray that evidence most appropriately?
The definition of validity, as well as formal sets of criteria, have been proposed, including use of the proportion explained, jointly the within-treatment partial association of true and surrogate responses, and the treatment effect on the surrogate relative to that on the true outcome. In a multi-centre setting, these quantities can be generalized to individual-level and trial-level measures of surrogacy.
Consequently, a meta-analytic framework studying surrogacy at both the trial and individual-patient levels has been proposed. A number of variations of this theme have been developed, depending on the type of endpoint for the true and surrogate endpoint and on the focus of the evaluation exercise.
The framework commonly used will be sketched, also against the background of alternatives. A perspective will be given on further and ongoing developments. Specific attention will be given to promise and challenges in the context of rare diseases.
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