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Statistical evaluation of biomarkers as surrogate endpoints: a literature review

Authors

  • Christopher J. Weir,

    Corresponding author
    1. Division of Cardiovascular and Medical Sciences, University of Glasgow, Gardiner Institute, Western Infirmary, Glasgow, G11 6NT, U.K.
    2. Robertson Centre for Biostatistics, University of Glasgow, University Avenue, Glasgow, G12 8QQ, U.K.
    • Robertson Centre for Biostatistics, University of Glasgow, University Avenue, Glasgow, G12 8QQ, U.K.
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  • Rosalind J. Walley

    1. Nonclinical Statistics, Pfizer Global Research and Development, Ramsgate Road, Sandwich, Kent, CT13 9NJ, U.K.
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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. Copyright © 2005 John Wiley & Sons, Ltd.

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