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Statistical Validation of Surrogate Markers in Clinical Trials

In: Developments in Statistical Evaluation of Clinical Trials

Author

Listed:
  • Ariel Alonso

    (Maastricht University, Department of Methodology and Statistics)

  • Geert Molenberghs

    (Universiteit Hasselt, I-BioStat
    KU Leuven - University of Leuven)

  • Gerard van Breukelen

    (Maastricht University, Department of Methodology and Statistics)

Abstract

The increasing cost of drug development has raised the demand on the use of biomarkers as surrogate endpoints for the evaluation of new drugs in clinical trials. However, failed past attempts to use surrogate endpoints made it clear that, before deciding on the use of a candidate surrogate endpoint, it is of the utmost importance to investigate its validity. Such validation process has proven challenging for conceptual and practical reasons. In the present chapter, some of the statistical methods introduced for the evaluation of surrogate markers will be discussed. Emphasis will be made on the so-called meta-analytic approach and its information-theoretic version, where information from several units is combined to carry out the validation exercise. The methods will be illustrated using a case study in ophthalmology.

Suggested Citation

  • Ariel Alonso & Geert Molenberghs & Gerard van Breukelen, 2014. "Statistical Validation of Surrogate Markers in Clinical Trials," Springer Books, in: Kees van Montfort & Johan Oud & Wendimagegn Ghidey (ed.), Developments in Statistical Evaluation of Clinical Trials, edition 127, chapter 0, pages 227-246, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-55345-5_13
    DOI: 10.1007/978-3-642-55345-5_13
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