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A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper


  • Mikyung Kelly Seo

    (University of Cambridge
    London School of Hygiene and Tropical Medicine
    University of Bergen
    Imperial College London)

  • Mark Strong

    (University of Sheffield)


Despite the increasing number of potential biomarkers identified in laboratories and reported in much literature, the adoption of biomarkers routinely available in clinical practice to inform treatment decisions is very limited. Reimbursement decisions for new health technologies are often informed by economic evaluations; however, economic evaluations of diagnostics/testing technologies, such as companion biomarker tests, are far less frequently reported than drugs. Furthermore, few countries provide the health economic evaluation methods guide specific to co-dependent technologies such as companion diagnostics or precision medicines. Therefore, this paper aims to guide the process of the development of cost-effectiveness models of cancer biomarkers for targeted therapies, focusing on companion diagnostics. This tutorial paper provides practical guidance on how to conduct economic evaluations of cancer biomarkers and how to model the characteristics of the biomarker tests as part of the value for money of corresponding targeted therapies. This paper presents a brief introduction to the methods and data requirements, a step-by-step guide to constructing a health economic model of companion cancer biomarkers, and a discussion of issues that arise in their application to healthcare decision making. This practical guidance is provided in R, and worked examples are provided in this paper with R codes in the accompanying electronic supplementary material.

Suggested Citation

  • Mikyung Kelly Seo & Mark Strong, 2021. "A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper," PharmacoEconomics, Springer, vol. 39(12), pages 1373-1381, December.
  • Handle: RePEc:spr:pharme:v:39:y:2021:i:12:d:10.1007_s40273-021-01069-8
    DOI: 10.1007/s40273-021-01069-8

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    References listed on IDEAS

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