IDEAS home Printed from https://ideas.repec.org/a/spr/pharmo/v8y2024i2d10.1007_s41669-023-00443-w.html
   My bibliography  Save this article

Health State Utilities Associated with False-Positive Cancer Screening Results

Author

Listed:
  • Louis S. Matza

    (Evidera)

  • Timothy A. Howell

    (Evidera)

  • Eric T. Fung

    (GRAIL, LLC., a subsidiary of Illumina Inc.)

  • Sam M. Janes

    (University College London)

  • Michael Seiden

    (GRAIL, LLC.)

  • Allan Hackshaw

    (University College London)

  • Lincoln Nadauld

    (Intermountain Healthcare)

  • Hayley Karn

    (Evidera)

  • Karen C. Chung

    (GRAIL, LLC., a subsidiary of Illumina Inc.)

Abstract

Introduction Early cancer detection can significantly improve patient outcomes and reduce mortality rates. Novel cancer screening approaches, including multi-cancer early detection tests, have been developed. Cost-utility analyses will be needed to examine their value, and these models require health state utilities. The purpose of this study was to estimate the disutility (i.e., decrease in health state utility) associated with false-positive cancer screening results. Methods In composite time trade-off interviews using a 1-year time horizon, UK general population participants valued 10 health state vignettes describing cancer screening with true-negative or false-positive results. Each false-positive vignette described a common diagnostic pathway following a false-positive result suggesting lung, colorectal, breast, or pancreatic cancer. Every pathway ended with a negative result (no cancer detected). The disutility of each false positive was calculated as the difference between the true-negative and each false-positive health state, and because of the 1-year time horizon, each disutility can be interpreted as a quality-adjusted life-year decrement associated with each type of false-positive experience. Results A total of 203 participants completed interviews (49.8% male; mean age = 42.0 years). The mean (SD) utility for the health state describing a true-negative result was 0.958 (0.065). Utilities for false-positive health states ranged from 0.847 (0.145) to 0.932 (0.059). Disutilities for false positives ranged from − 0.031 to − 0.111 (− 0.041 to − 0.111 for lung cancer; − 0.079 for colorectal cancer; − 0.031 to − 0.067 for breast cancer; − 0.048 to − 0.088 for pancreatic cancer). Conclusion All false-positive results were associated with a disutility. Greater disutility was associated with more invasive follow-up diagnostic procedures, longer duration of uncertainty regarding the eventual diagnosis, and perceived severity of the suspected cancer type. Utility values estimated in this study would be useful for economic modeling examining the value of cancer screening procedures.

Suggested Citation

  • Louis S. Matza & Timothy A. Howell & Eric T. Fung & Sam M. Janes & Michael Seiden & Allan Hackshaw & Lincoln Nadauld & Hayley Karn & Karen C. Chung, 2024. "Health State Utilities Associated with False-Positive Cancer Screening Results," PharmacoEconomics - Open, Springer, vol. 8(2), pages 263-276, March.
    • Handle: RePEc:spr:pharmo:v:8:y:2024:i:2:d:10.1007_s41669-023-00443-w
    DOI: 10.1007/s41669-023-00443-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41669-023-00443-w
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1007/s41669-023-00443-w?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
    ---><---

    References listed on IDEAS

    as
    1. Linda D. Mackeigan & Bernie J. O'Brien & Paul I. Oh, 1999. "Holistic versus Composite Preferences for Lifetime Treatment Sequences for Type 2 Diabetes," Medical Decision Making, , vol. 19(2), pages 113-120, April.
    2. Johnston, Katharine & Brown, Jackie & Gerard, Karen & O'Hanlon, Moira & Morton, Alison, 1998. "Valuing temporary and chronic health states associated with breast screening," Social Science & Medicine, Elsevier, vol. 47(2), pages 213-222, July.
    3. Karen Gerard & Katharine Johnston & Jackie Brown, 1999. "The role of a pre‐scored multi‐attribute health classification measure in validating condition‐specific health state descriptions," Health Economics, John Wiley & Sons, Ltd., vol. 8(8), pages 685-699, December.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    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.
    3. Timothy A. Howell & Louis S. Matza & Monika P. Jun & Jacob Garcia & Annette Powers & David G. Maloney, 2022. "Health State Utilities for Adverse Events Associated with Chimeric Antigen Receptor T-Cell Therapy in Large B-Cell Lymphoma," PharmacoEconomics - Open, Springer, vol. 6(3), pages 367-376, May.
    4. Sylvia J.T. Jansen & Anne M. Stiggelbout & Peter P. Wakker & Marianne A. Nooij & Evert M. Noordijk & Job Kievit, 2000. "Unstable Preferences:," Medical Decision Making, , vol. 20(1), pages 62-71, January.
    5. Peep F. M. Stalmeier, 2002. "Discrepancies between Chained and Classic Utilities Induced by Anchoring with Occasional Adjustments," Medical Decision Making, , vol. 22(1), pages 53-64, February.
    6. Lisa Prosser & James Hammitt & Ron Keren, 2007. "Measuring Health Preferences for Use in Cost-Utility and Cost-Benefit Analyses of Interventions in Children," PharmacoEconomics, Springer, vol. 25(9), pages 713-726, September.
    7. A. Pickard & Caitlyn Wilke & Hsiang-Wen Lin & Andrew Lloyd, 2007. "Health Utilities Using the EQ-5D in Studies of Cancer," PharmacoEconomics, Springer, vol. 25(5), pages 365-384, May.
    8. Anne Spencer, 2000. "Testing the Additive Independence Assumption in the QALY Model," Working Papers 427, Queen Mary University of London, School of Economics and Finance.
    9. Karen Gerard & Katharine Johnston & Jackie Brown, 1999. "The role of a pre‐scored multi‐attribute health classification measure in validating condition‐specific health state descriptions," Health Economics, John Wiley & Sons, Ltd., vol. 8(8), pages 685-699, December.
    10. Jing Shen & Matthew Breckons & Luke Vale & Robert Pickard, 2019. "Using Time Trade-Off Methods to Elicit Short-Term Utilities Associated with Treatments for Bulbar Urethral Stricture," PharmacoEconomics - Open, Springer, vol. 3(4), pages 551-558, December.
    11. Kristina Secnik & Louis S. Matza & Suzi Cottrell & Eric Edgell & Dominic Tilden & Sally Mannix, 2005. "Health State Utilities for Childhood Attention-Deficit/Hyperactivity Disorder Based on Parent Preferences in the United Kingdom," Medical Decision Making, , vol. 25(1), pages 56-70, January.
    12. Anne Spencer, 2004. "The implications of linking questions within the SG and TTO methods," Health Economics, John Wiley & Sons, Ltd., vol. 13(8), pages 807-818, August.
    13. Mirjam Locadia & Peep F. M. Stalmeier & Frans J. Oort & Martin H. Prins & Mirjam A. G. Sprangers & Patrick M. M. Bossuyt, 2004. "A Comparison of 3 Valuation Methods for Temporary Health States in Patients Treated with Oral Anticoagulants," Medical Decision Making, , vol. 24(6), pages 625-633, November.
    14. Peter P. Wakker & Sylvia J. T. Jansen & Anne M. Stiggelbout, 2004. "Anchor Levels as a New Tool for the Theory and Measurement of Multiattribute Utility," Decision Analysis, INFORMS, vol. 1(4), pages 217-234, December.
    15. Kristina Boye & Louis Matza & Kimberly Walter & Kate Brunt & Andrew Palsgrove & Aodan Tynan, 2011. "Utilities and disutilities for attributes of injectable treatments for type 2 diabetes," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(3), pages 219-230, June.
    16. Anne Spencer, 2000. "Testing the Additive Independence Assumption in the QALY Model," Working Papers 427, Queen Mary University of London, School of Economics and Finance.

    More about this item

    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:pharmo:v:8:y:2024:i:2:d:10.1007_s41669-023-00443-w. 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.