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Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments

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  • N. Morrish

    (Public Health Economics Group, Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK)

  • T. Snowsill

    (Health Economics Group, Health and Community Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK)

  • S. Dodman

    (University of Exeter, Exeter, UK)

  • A. Medina-Lara

    (Public Health Economics Group, Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK)

Abstract

Background Understanding service user preferences is key to effective health care decision making and efficient resource allocation. It is of particular importance in the management of high-risk patients in whom predictive genetic testing can alter health outcomes. Purpose This review aims to identify the relative importance and willingness to pay for attributes of genetic testing in hereditary cancer syndromes. Data Sources Searches were conducted in Medline, Embase, PsycINFO, HMIC, Web of Science, and EconLit using discrete choice experiment (DCE) terms combined with terms related to hereditary cancer syndromes, malignancy synonyms, and genetic testing. Study Selection Following independent screening by 3 reviewers, 7 studies fulfilled the inclusion criteria, being a DCE investigating patient or public preferences related to predictive genetic testing for hereditary cancer syndromes. Data Extraction Extracted data included study and respondent characteristics, DCE attributes and levels, methods of data analysis and interpretation, and key study findings. Data Synthesis Studies covered colorectal, breast, and ovarian cancer syndromes. Results were summarized in a narrative synthesis and the quality assessed using the Lancsar and Louviere framework. Limitations This review focuses only on DCE design and testing for hereditary cancer syndromes rather than other complex diseases. Challenges also arose from heterogeneity in attributes and levels. Conclusions Test effectiveness and detection rates were consistently important to respondents and thus should be prioritized by policy makers. Accuracy, cost, and wait time, while also important, showed variation between studies, although overall reduction in cost may improve uptake. Patients and the public would be willing to pay for improved detection and clinician over insurance provider involvement. Future studies should seek to contextualize findings by considering the impact of sociodemographic characteristics, health system coverage, and insurance policies on preferences. Highlights Test effectiveness and detection rates are consistently important to respondents in genetic testing for hereditary cancer syndromes. Reducing the cost of genetic testing for hereditary cancer syndromes may improve uptake. Individuals are most willing to pay for a test that improves detection rates, identifies multiple cancers, and for which results are shared with a doctor rather than with an insurance provider.

Suggested Citation

  • N. Morrish & T. Snowsill & S. Dodman & A. Medina-Lara, 2024. "Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments," Medical Decision Making, , vol. 44(3), pages 252-268, April.
    • Handle: RePEc:sae:medema:v:44:y:2024:i:3:p:252-268
    DOI: 10.1177/0272989X241227425
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    References listed on IDEAS

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    1. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    2. Daly, Andrew & Dekker, Thijs & Hess, Stephane, 2016. "Dummy coding vs effects coding for categorical variables: Clarifications and extensions," Journal of choice modelling, Elsevier, vol. 21(C), pages 36-41.
    3. Sara J. Knight & Ateesha F. Mohamed & Deborah A. Marshall & Uri Ladabaum & Kathryn A. Phillips & Judith M. E. Walsh, 2015. "Value of Genetic Testing for Hereditary Colorectal Cancer in a Probability-Based US Online Sample," Medical Decision Making, , vol. 35(6), pages 734-744, August.
    4. Emily Lancsar & Elizabeth Savage, 2004. "Deriving welfare measures from discrete choice experiments: inconsistency between current methods and random utility and welfare theory," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 901-907, September.
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