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Updated: Aug 15, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Statistical evaluation of biomarkers as surrogate endpoints: a literature review
Christopher J Weir1, Rosalind J Walley
1Division of Cardiovascular and Medical Sciences, University of Glasgow, Gardiner Institute, Western Infirmary, Glasgow, G11 6NT, UK. c.weir@stats.gla.ac.uk
Abstract:
A valid surrogate endpoint allows correct inference to be drawn regarding the effect of an intervention on the unobserved true clinical endpoint of interest. The perceived practical and ethical advantages of substituting a surrogate endpoint for a clinical endpoint have led to a considerable number of statistical methods being proposed for the evaluation of a biomarker as a surrogate endpoint. We review the main statistical schools of thought which have developed and consider how the validation process might be arranged within the regulatory and practical constraints of the drug development process. We conclude by assessing which of the candidate statistical methods offer the best approach for surrogate endpoint evaluation.
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