Abstract
Surrogate markers are often used in clinical trials settings when obtaining a final outcome to evaluate the effectiveness of a treatment requires a long wait, is expensive to obtain, or both. Formal definitions of surrogate marker quality resulting from a large variety of estimation approaches have been proposed over the years. I review this work, with a particular focus on approaches that use the causal inference paradigm, as these conceptualize a good marker as one in the causal pathway between the treatment and outcome. I also focus on efforts to evaluate the risk of a surrogate paradox, a damaging situation where the surrogate is positively associated with the outcome, and the causal effect of the treatment on the surrogate is in a helpful direction, but the ultimate causal effect of the treatment on the outcome is harmful. I then review some recent work in robust surrogate marker estimation and conclude with a discussion and suggestions for future research.
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CITATION STYLE
Elliott, M. R. (2023, March 10). Surrogate Endpoints in Clinical Trials. Annual Review of Statistics and Its Application. Annual Reviews Inc. https://doi.org/10.1146/annurev-statistics-032921-035359
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