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Cost-Effectiveness Models in Breast Cancer Screening in the General Population: A Systematic Review

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  • Irmgard C. Schiller-Frühwirth

    (Main Association of Austrian Social Security Institutions
    University for Health Sciences, Medical Informatics and Technology)

  • Beate Jahn

    (University for Health Sciences, Medical Informatics and Technology
    ONCOTYROL-Center for Personalized Cancer Medicine)

  • Marjan Arvandi

    (University for Health Sciences, Medical Informatics and Technology)

  • Uwe Siebert

    (University for Health Sciences, Medical Informatics and Technology
    ONCOTYROL-Center for Personalized Cancer Medicine
    Massachusetts General Hospital, Harvard Medical School
    Harvard T.H. Chan School of Public Health)

Abstract

Background Many Western countries have long-established population-based mammography screening programs. Prior to implementing these programs, decision-analytic modeling was widely used to inform decisions. Objective The aim of this study was to perform a systematic review of cost-effectiveness models in breast cancer screening in the general population to analyze their structural and methodological approaches. Methods A systematic literature search for health economic models was performed in the electronic databases MEDLINE (Ovid), EMBASE, CRD Databases, Cochrane Library, and EconLit in August 2011 with updates in June 2013, April 2015, and November 2016. To assess studies systematically, a standardized form was applied to extract relevant information that was then summarized in evidence tables. Results Thirty-five studies were included; 27 state-transition models were analyzed using cohort (n = 12) and individual-level simulation (n = 15). Twenty-one studies modeled the natural history of breast cancer and predicted mortality as a function of the early detection modality. The models employed different assumptions regarding ductal carcinoma in situ. Thirteen studies performed cost-utility analyses with different sources for utility values, but assumptions were often made about utility weights. Twenty-two models did not report any validation. Conclusion State-transition modeling was the most frequently applied analytic approach. Different methods in modeling the progression of ductal carcinoma in situ to invasive cancer were identified because there is currently no agreement on the biological behavior of noninvasive breast cancer. Main weaknesses were the lack of precise utility estimates and insufficient reporting of validation. Sensitivity analyses of assumptions regarding ductal carcinoma in situ and in particular adequate validation are critical to minimize the risk of biased model outcomes.

Suggested Citation

  • Irmgard C. Schiller-Frühwirth & Beate Jahn & Marjan Arvandi & Uwe Siebert, 2017. "Cost-Effectiveness Models in Breast Cancer Screening in the General Population: A Systematic Review," Applied Health Economics and Health Policy, Springer, vol. 15(3), pages 333-351, June.
    • Handle: RePEc:spr:aphecp:v:15:y:2017:i:3:d:10.1007_s40258-017-0312-3
    DOI: 10.1007/s40258-017-0312-3
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    References listed on IDEAS

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    1. Thomas A. Trikalinos & Uwe Siebert & Joseph Lau, 2009. "Decision-Analytic Modeling to Evaluate Benefits and Harms of Medical Tests: Uses and Limitations," Medical Decision Making, , vol. 29(5), pages 22-29, September.
    2. Szeto, Kam Leong & Devlin, Nancy J., 1996. "The cost-effectiveness of mammography screening: evidence from a microsimulation model for New Zealand," Health Policy, Elsevier, vol. 38(2), pages 101-115, November.
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    4. Hall, Jane & Gerard, Karen & Salkeld, Glenn & Richardson, Jeff, 1992. "A cost utility analysis of mammography screening in Australia," Social Science & Medicine, Elsevier, vol. 34(9), pages 993-1004, May.
    5. Paul Kind & Geoffrey Hardman & Susan Macran, 1999. "UK population norms for EQ-5D," Working Papers 172chedp, Centre for Health Economics, University of York.
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    1. Michael J. Zoratti & A. Simon Pickard & Peep F. M. Stalmeier & Daniel Ollendorf & Andrew Lloyd & Kelvin K W Chan & Don Husereau & John E. Brazier & Murray Krahn & Mitchell Levine & Lehana Thabane & Fe, 2021. "Evaluating the conduct and application of health utility studies: a review of critical appraisal tools and reporting checklists," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 723-733, July.
    2. Lin Li & J L (Hans) Severens & Olena Mandrik, 2019. "Disutility associated with cancer screening programs: A systematic review," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-17, July.
    3. Isaac Corro Ramos & Martine Hoogendoorn & Maureen P. M. H. Rutten-van Mölken, 2020. "How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease," Medical Decision Making, , vol. 40(5), pages 619-632, July.
    4. Bromley, Hannah L. & Petrie, Dennis & Mann, G.Bruce & Nickson, Carolyn & Rea, Daniel & Roberts, Tracy E., 2019. "Valuing the health states associated with breast cancer screening programmes: A systematic review of economic measures," Social Science & Medicine, Elsevier, vol. 228(C), pages 142-154.
    5. Nikolai Mühlberger & Gaby Sroczynski & Artemisa Gogollari & Beate Jahn & Nora Pashayan & Ewout Steyerberg & Martin Widschwendter & Uwe Siebert, 2021. "Cost effectiveness of breast cancer screening and prevention: a systematic review with a focus on risk-adapted strategies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(8), pages 1311-1344, November.

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