IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v20y2019i5d10.1007_s10198-019-01038-1.html
   My bibliography  Save this article

Economic modeling of risk-adapted screen-and-treat strategies in women at high risk for breast or ovarian cancer

Author

Listed:
  • Dirk Müller

    (The University Hospital of Cologne (AöR))

  • Marion Danner

    (The University Hospital of Cologne (AöR))

  • Rita Schmutzler

    (University Hospital Cologne)

  • Christoph Engel

    (University of Leipzig)

  • Kirsten Wassermann

    (University Hospital Cologne)

  • Björn Stollenwerk

    (German Research Center for Environmental Health)

  • Stephanie Stock

    (The University Hospital of Cologne (AöR))

  • Kerstin Rhiem

    (University Hospital Cologne)

Abstract

Background The ‘German Consortium for Hereditary Breast and Ovarian Cancer’ (GC-HBOC) offers women with a family history of breast and ovarian cancer genetic counseling. The aim of this modeling study was to evaluate the cost-effectiveness of genetic testing for BRCA 1/2 in women with a high familial risk followed by different preventive interventions (intensified surveillance, risk-reducing bilateral mastectomy, risk-reducing bilateral salpingo-oophorectomy, or both mastectomy and salpingo-oophorectomy) compared to no genetic test. Methods A Markov model with a lifelong time horizon was developed for a cohort of 35-year-old women with a BRCA 1/2 mutation probability of ≥ 10%. The perspective of the German statutory health insurance (SHI) was adopted. The model included the health states ‘well’ (women with increased risk), ‘breast cancer without metastases’, ‘breast cancer with metastases’, ‘ovarian cancer’, ‘death’, and two post (non-metastatic) breast or ovarian cancer states. Outcomes were costs, quality of life years gained (QALYs) and life years gained (LYG). Important data used for the model were obtained from 4380 women enrolled in the GC-HBOC. Results Compared with the no test strategy, genetic testing with subsequent surgical and non-surgical treatment options provided to women with deleterious BRCA 1 or 2 mutations resulted in additional costs of €7256 and additional QALYs of 0,43 (incremental cost-effectiveness ratio of €17,027 per QALY; cost per LYG: €22,318). The results were robust in deterministic and probabilistic sensitivity analyses. Conclusion The provision of genetic testing to high-risk women with a BRCA1 and two mutation probability of ≥ 10% based on the individual family cancer history appears to be a cost-effective option for the SHI.

Suggested Citation

  • Dirk Müller & Marion Danner & Rita Schmutzler & Christoph Engel & Kirsten Wassermann & Björn Stollenwerk & Stephanie Stock & Kerstin Rhiem, 2019. "Economic modeling of risk-adapted screen-and-treat strategies in women at high risk for breast or ovarian cancer," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 739-750, July.
    • Handle: RePEc:spr:eujhec:v:20:y:2019:i:5:d:10.1007_s10198-019-01038-1
    DOI: 10.1007/s10198-019-01038-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-019-01038-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10198-019-01038-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. John A. Nyman, 2004. "Should the consumption of survivors be included as a cost in cost–utility analysis?," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 417-427, May.
    2. Peasgood, T & Ward, S & Brazier, J, 2010. "A review and meta-analysis of health state utility values in breast cancer," MPRA Paper 29950, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aruni Ghose & Anita Bolina & Ishika Mahajan & Syed Ahmer Raza & Miranda Clarke & Abhinanda Pal & Elisabet Sanchez & Kathrine Sofia Rallis & Stergios Boussios, 2022. "Hereditary Ovarian Cancer: Towards a Cost-Effective Prevention Strategy," IJERPH, MDPI, vol. 19(19), pages 1-18, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pieter H. M. van Baal & Talitha L. Feenstra & Rudolf T. Hoogenveen & G. Ardine de Wit & Werner B. F. Brouwer, 2007. "Unrelated medical care in life years gained and the cost utility of primary prevention: in search of a ‘perfect’ cost–utility ratio," Health Economics, John Wiley & Sons, Ltd., vol. 16(4), pages 421-433, April.
    2. Bengt Liljas, 2011. "Welfare, QALYs, and costs – a comment," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 68-72, January.
    3. Douglas Lundin & Joakim Ramsberg, 2008. "On survival consumption costs – a reply to Nyman," Health Economics, John Wiley & Sons, Ltd., vol. 17(2), pages 293-297, February.
    4. Afschin Gandjour & Dirk Müller, 2014. "Ethical Objections Against Including Life-Extension Costs in Cost-Effectiveness Analysis: A Consistent Approach," Applied Health Economics and Health Policy, Springer, vol. 12(5), pages 471-476, October.
    5. Micah Rose & Stephen Rice & Dawn Craig, 2018. "Does Methodological Guidance Produce Consistency? A Review of Methodological Consistency in Breast Cancer Utility Value Measurement in NICE Single Technology Appraisals," PharmacoEconomics - Open, Springer, vol. 2(2), pages 97-107, June.
    6. Pieter H. M. van Baal & Talitha L. Feenstra & Johan J. Polder & Rudolf T. Hoogenveen & Werner B. F. Brouwer, 2011. "Economic evaluation and the postponement of health care costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(4), pages 432-445, April.
    7. Feng Xie & Michael Zoratti & Kelvin Chan & Don Husereau & Murray Krahn & Oren Levine & Tammy Clifford & Holger Schunemann & Gordon Guyatt, 2019. "Toward a Centralized, Systematic Approach to the Identification, Appraisal, and Use of Health State Utility Values for Reimbursement Decision Making: Introducing the Health Utility Book (HUB)," Medical Decision Making, , vol. 39(4), pages 371-379, May.
    8. Linda M. Vries & Pieter H. M. Baal & Werner B. F. Brouwer, 2019. "Future Costs in Cost-Effectiveness Analyses: Past, Present, Future," PharmacoEconomics, Springer, vol. 37(2), pages 119-130, February.
    9. Basu, Anirban, 2020. "A welfare-theoretic model consistent with the practice of cost-effectiveness analysis and its implications," Journal of Health Economics, Elsevier, vol. 70(C).
    10. Erik Nord & Christoffer Lamøy, 2018. "Including Future Consumption and Production in Economic Evaluation of Interventions that Save Life-Years: Commentary," PharmacoEconomics - Open, Springer, vol. 2(4), pages 357-358, December.
    11. John A. Nyman, 2011. "Measurement of QALYS and the welfare implications of survivor consumption and leisure forgone," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 56-67, January.
    12. Gregory Katz & Olivier Romano & Cyril Foa & Anne-Lise Vataire & Jean-Victor Chantelard & Robert Hervé & Hugues Barletta & Axel Durieux & Jean-Pierre Martin & Rémy Salmon, 2015. "Economic Impact of Gene Expression Profiling in Patients with Early-Stage Breast Cancer in France," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-15, June.
    13. Quang A. Le, 2016. "Structural Uncertainty of Markov Models for Advanced Breast Cancer," Medical Decision Making, , vol. 36(5), pages 629-640, July.
    14. Liqun Liu & Andrew J. Rettenmaier & Thomas R. Saving, 2008. "Longevity bias in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 17(4), pages 523-534, April.
    15. Dieter Tscheulin & Florian Drevs, 2010. "The relevance of unrelated costs internal and external to the healthcare sector to the outcome of a cost-comparison analysis of secondary prevention: the case of general colorectal cancer screening in," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 141-150, April.
    16. Alec Morton & Amanda I. Adler & David Bell & Andrew Briggs & Werner Brouwer & Karl Claxton & Neil Craig & Alastair Fischer & Peter McGregor & Pieter van Baal, 2016. "Unrelated Future Costs and Unrelated Future Benefits: Reflections on NICE Guide to the Methods of Technology Appraisal," Health Economics, John Wiley & Sons, Ltd., vol. 25(8), pages 933-938, August.
    17. Jiryoun Gong & Juhee Han & Donghwan Lee & Seungjin Bae, 2020. "A Meta-Regression Analysis of Utility Weights for Breast Cancer: The Power of Patients’ Experience," IJERPH, MDPI, vol. 17(24), pages 1-16, December.
    18. Afschin Gandjour, 2009. "Aging diseases – do they prevent preventive health care from saving costs?," Health Economics, John Wiley & Sons, Ltd., vol. 18(3), pages 355-362, March.
    19. Patricia Blank & Martin Filipits & Peter Dubsky & Florian Gutzwiller & Michael Lux & Jan Brase & Karsten Weber & Margaretha Rudas & Richard Greil & Sibylle Loibl & Thomas Szucs & Ralf Kronenwett & Mat, 2015. "Cost-Effectiveness Analysis of Prognostic Gene Expression Signature-Based Stratification of Early Breast Cancer Patients," PharmacoEconomics, Springer, vol. 33(2), pages 179-190, February.
    20. Nasuh C. Büyükkaramikli & Saskia Groot & Rob Riemsma & Debra Fayter & Nigel Armstrong & Piet Portegijs & Steven Duffy & Jos Kleijnen & Maiwenn J. Al, 2019. "Ribociclib with an Aromatase Inhibitor for Previously Untreated, HR-Positive, HER2-Negative, Locally Advanced or Metastatic Breast Cancer: An Evidence Review Group Perspective of a NICE Single Technol," PharmacoEconomics, Springer, vol. 37(2), pages 141-153, February.

    More about this item

    Keywords

    Cost-effectiveness; Economic modeling; Genetic testing; Breast cancer; Risk-reducing surgery; BRCA;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:eujhec:v:20:y:2019:i:5:d:10.1007_s10198-019-01038-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.