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Genetic-Guided Pharmacotherapy for Atrial Fibrillation: A Systematic and Critical Review of Economic Evaluations

  • Author Footnotes
    ∗ Ahmad Amir Kamil and Ka Keat Lim contributed equally to this manuscript.
    Ahmad Amir Kamil
    Footnotes
    ∗ Ahmad Amir Kamil and Ka Keat Lim contributed equally to this manuscript.
    Affiliations
    School of Life Course & Population Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, England, UK
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  • Author Footnotes
    ∗ Ahmad Amir Kamil and Ka Keat Lim contributed equally to this manuscript.
    Ka Keat Lim
    Footnotes
    ∗ Ahmad Amir Kamil and Ka Keat Lim contributed equally to this manuscript.
    Affiliations
    School of Life Course & Population Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, England, UK

    National Institute for Health Research Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, England, UK
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  • Rositsa Koleva-Kolarova
    Affiliations
    Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, England, UK
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  • Philip Chowienczyk
    Affiliations
    National Institute for Health Research Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, England, UK

    Cardiovascular Division, Department of Clinical Pharmacology, King’s College London and St Thomas’ Hospital Medical School, London, UK
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  • Charles D.A. Wolfe
    Affiliations
    School of Life Course & Population Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, England, UK

    National Institute for Health Research Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, England, UK

    National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care, South London, England, UK
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  • Julia Fox-Rushby
    Correspondence
    Correspondence: Julia Fox-Rushby, Professor of Health Economics, School of Life Course & Population Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, England, United Kingdom.
    Affiliations
    School of Life Course & Population Sciences, Faculty of Life Sciences & Medicine, King’s College London, London, England, UK

    National Institute for Health Research Biomedical Research Centre, Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, England, UK
    Search for articles by this author
  • Author Footnotes
    ∗ Ahmad Amir Kamil and Ka Keat Lim contributed equally to this manuscript.
Published:December 02, 2021DOI:https://doi.org/10.1016/j.jval.2021.09.013

      Highlights

      • What is already known about the topic? Clinical management of atrial fibrillation (AF) can be stratified using 2 types of genetic information—genes associated with a higher risk of AF and genes that modulate patients’ response to therapy. Although economic evidence of genetic-guided pharmacotherapy (PGx) for AF has been building up in the past decade, there has been no synthesis of the evidence to advise the value of PGx testing for AF in clinical practice.
      • What does the paper add to existing knowledge? Our review (1) suggests PGx testing to determine coumadin dosing is more costly and more effective than coumadin standard/clinical dosing but less costly and less effective than direct-acting anticoagulants, (2) identifies 61 influential variables that change base-case conclusions that should be evaluated in future trials or models, (3) found 14 approaches to represent effect of PGx testing in model design and structural assumptions, (4) and found gaps in knowledge, reporting, and methodological quality.
      • What insights does the paper provide for informing healthcare-related decision making? Three strategies—standard/clinical coumadin dosing, PGx testing to determine coumadin dosing, and direct-acting anticoagulants—have increasingly higher effectiveness and higher cost. Countries with higher willingness-to-pay threshold values will be more able to afford the higher cost intervention per quality-adjusted life-year gained, provided they could overcome the implementation and ethical challenges. Several PGx testing interventions and comparators with scant evidence may require further studies to address their cost-effectiveness.

      Abstract

      Objectives

      This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.

      Methods

      From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.

      Results

      We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system’s perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients’ adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but less costly and less effective than standard DOAC dosing (14 of 14 comparisons). The remaining comparisons were too few to observe any trend. Of 61 variables influential in changing base-case conclusions, effectiveness of PGx testing was the most common (37%), accounted for in the models using time-based or medication-based approaches or relative risk. The cost of PGx testing has decreased and plateaued over time.

      Conclusions

      EEs to date only partially inform decisions on selecting optimal PGx testing for AF, because most evidence focuses on PGx testing to determine coumadin dosing, but less on other purposes. Future EE may refer to the list of influential variables and the approaches used to account for the effect of PGx testing to inform data collection and study design.

      Keywords

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