IDEAS home Printed from https://ideas.repec.org/a/spr/patien/v17y2024i3d10.1007_s40271-023-00670-7.html
   My bibliography  Save this article

Patients’ Preferences for Systemic Lupus Erythematosus Treatments—A Discrete Choice Experiment

Author

Listed:
  • Hannah Collacott

    (Evidera)

  • Andrea Phillips-Beyer

    (Innovus Consulting)

  • Nicolas Krucien

    (Evidera)

  • Bruno Flamion

    (Idorsia Pharmaceuticals Ltd)

  • Kevin Marsh

    (Evidera)

Abstract

Background Symptoms of systemic lupus erythematosus (SLE) vary between patients, but those of increased disease activity typically include musculoskeletal and mucocutaneous manifestations such as joint pain, swelling, and rashes. Several treatment options are available to patients with SLE with variable efficacy. Many treatments, especially corticosteroids, cause unwanted side effects, although little is currently known about patients’ preferences for treatments of SLE. Objective We aimed to identify which attributes of SLE treatment are valued by patients and to quantify their relative importance. Methods Adult participants with moderate-to-severe SLE were asked to make a series of choices between two hypothetical treatments in an online discrete choice experiment (DCE). A latent class model (LCL) was estimated to analyze choice data. Relative attribute importance (RAI) was calculated to determine the importance of each attribute to participants. Results A total of 342 participants from the USA completed the survey. A three-class LCL model was found to have the best fit. Class 1 (non-attenders) had non-significant preferences across all attributes. To achieve a better fit, a constrained LCL (cLCL) model was run with the two remaining classes. The most important attributes for participants in class 2 (benefit-seekers) were joint pain (RAI = 32.0%), non-joint pain (RAI = 21.8%), fatigue (RAI = 20.1%), and skin rashes and itching (RAI = 19.1%). The most important attributes for participants in class 3 (risk-avoiders) were risk of non-severe side effects from corticosteroids (RAI = 28.4%), risk of severe side effects from corticosteroids (RAI = 21.4%), and the risk of infections (RAI = 19.2%). Risk-avoiders were more likely to have been diagnosed with SLE for a longer period (>1 year) and were more likely to have experience with oral corticosteroids. Conclusions SLE patients fall into two groups with distinct preferences: benefit-seekers, who prioritize reducing the impact of disease symptoms, and risk-avoiders, who prioritize avoiding treatment risks. The implication of this finding will depend on the reasons for these differences, which warrant further research. Our study suggests that these differences arise due to the impact of disease and treatment experience on preferences. If so, well-informed patients may not be willing to tolerate the risks associated with oral corticosteroids in exchange for their benefits.

Suggested Citation

  • Hannah Collacott & Andrea Phillips-Beyer & Nicolas Krucien & Bruno Flamion & Kevin Marsh, 2024. "Patients’ Preferences for Systemic Lupus Erythematosus Treatments—A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 17(3), pages 287-300, May.
  • Handle: RePEc:spr:patien:v:17:y:2024:i:3:d:10.1007_s40271-023-00670-7
    DOI: 10.1007/s40271-023-00670-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40271-023-00670-7
    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/s40271-023-00670-7?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Lancsar, Emily & Louviere, Jordan & Flynn, Terry, 2007. "Several methods to investigate relative attribute impact in stated preference experiments," Social Science & Medicine, Elsevier, vol. 64(8), pages 1738-1753, April.
    2. Isaac M. Lipkus & Greg Samsa & Barbara K. Rimer, 2001. "General Performance on a Numeracy Scale among Highly Educated Samples," Medical Decision Making, , vol. 21(1), pages 37-44, February.
    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. Theresa Kuchler & Basit Zafar, 2019. "Personal Experiences and Expectations about Aggregate Outcomes," Journal of Finance, American Finance Association, vol. 74(5), pages 2491-2542, October.
    2. Ting Li & Robert J. Kauffman & Eric van Heck & Peter Vervest & Benedict G. C. Dellaert, 2014. "Consumer Informedness and Firm Information Strategy," Information Systems Research, INFORMS, vol. 25(2), pages 345-363, June.
    3. Pfarr, Christian & Schmid, Andreas, 2013. "The political economics of social health insurance: the tricky case of individuals’ preferences," MPRA Paper 44534, University Library of Munich, Germany.
    4. Andrea N. Natsky & Andrew Vakulin & Ching Li Chai-Coetzer & R. Doug McEvoy & Robert J. Adams & Billingsley Kaambwa, 2022. "Preferred Attributes of Care Pathways for Obstructive Sleep Apnoea from the Perspective of Diagnosed Patients and High-Risk Individuals: A Discrete Choice Experiment," Applied Health Economics and Health Policy, Springer, vol. 20(4), pages 597-607, July.
    5. Stephanie Knox & Rosalie Viney & Deborah Street & Marion Haas & Denzil Fiebig & Edith Weisberg & Deborah Bateson, 2012. "What’s Good and Bad About Contraceptive Products?," PharmacoEconomics, Springer, vol. 30(12), pages 1187-1202, December.
    6. Yaniv Hanoch & Talya Miron-Shatz & Mary Himmelstein, 2010. "Genetic testing and risk interpretation: How do women understand lifetime risk results?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(2), pages 116-123, April.
    7. Ralph Stevens & Jennifer Alonso Garcia & Hazel Bateman & Arthur van Soest & Johan Bonekamp, 2022. "Saving preferences after retirement," ULB Institutional Repository 2013/342267, ULB -- Universite Libre de Bruxelles.
    8. Cathy Anne Pinto & Gin Nie Chua & John F. P. Bridges & Ella Brookes & Johanna Hyacinthe & Tommi Tervonen, 2022. "Comparing Patient Preferences for Antithrombotic Treatment During the Acute and Chronic Phases of Myocardial Infarction: A Discrete-Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 15(2), pages 255-266, March.
    9. repec:cup:judgdm:v:14:y:2019:i:3:p:234-279 is not listed on IDEAS
    10. Diego Fernandez-Duque & Timothy Wifall, 2007. "Actor/observer asymmetry in risky decision making," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 2, pages 1-8, February.
    11. Hazel Bateman & Christine Eckert & Fedor Iskhakov & Jordan Louviere & Stephen Satchell & Susan Thorp, 2017. "Default and naive diversification heuristics in annuity choice," Australian Journal of Management, Australian School of Business, vol. 42(1), pages 32-57, February.
    12. Richard Norman & Jane Hall & Deborah Street & Rosalie Viney, 2013. "Efficiency And Equity: A Stated Preference Approach," Health Economics, John Wiley & Sons, Ltd., vol. 22(5), pages 568-581, May.
    13. Mark A. Andor & Thomas K. Bauer & Jana Eßer & Christoph M. Schmidt & Lukas Tomberg, 2025. "Who Gets Vaccinated? Cognitive and Non‐Cognitive Predictors of Individual Behaviour in Pandemics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 87(3), pages 562-585, June.
    14. David Ronayne & Roberto Veneziani & William R. Zame, 2022. "Do Decision Makers Have Subjective Probabilities? An Experimental Test," Working Papers 940, Queen Mary University of London, School of Economics and Finance.
    15. repec:cup:judgdm:v:9:y:2014:i:5:p:420-432 is not listed on IDEAS
    16. repec:cup:judgdm:v:15:y:2020:i:1:p:93-111 is not listed on IDEAS
    17. Bleemer, Zachary & Zafar, Basit, 2018. "Intended college attendance: Evidence from an experiment on college returns and costs," Journal of Public Economics, Elsevier, vol. 157(C), pages 184-211.
    18. Jennifer Alonso Garcia & Hazel Bateman & Johan Bonekamp & Ralph Stevens, 2017. "Retirement drawdown defaults: the role of implied endorsement," ULB Institutional Repository 2013/300025, ULB -- Universite Libre de Bruxelles.
    19. Antonini, Marcello & Genie, Mesfin G. & Attwell, Katie & Attema, Arthur E. & Ward, Jeremy K. & Melegaro, Alessia & Torbica, Aleksandra & Kelly, Brian & Berardi, Chiara & Sequeira, Ana Rita & McGregor,, 2025. "Are we ready for the next pandemic? Public preferences and trade-offs between vaccine characteristics and societal restrictions across 21 countries," Social Science & Medicine, Elsevier, vol. 366(C).
    20. Shehely Parvin & Paul Wang & Jashim Uddin, 2016. "Using best-worst scaling method to examine consumers’ value preferences: A multidimensional perspective," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1199110-119, December.
    21. Branden B. Johnson & Adam M. Finkel, 2016. "Public Perceptions of Regulatory Costs, Their Uncertainty and Interindividual Distribution," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1148-1170, June.
    22. Garcia-Retamero, Rocio & Hoffrage, Ulrich, 2013. "Visual representation of statistical information improves diagnostic inferences in doctors and their patients," Social Science & Medicine, Elsevier, vol. 83(C), pages 27-33.
    23. repec:plo:pone00:0156629 is not listed on IDEAS
    24. repec:cup:judgdm:v:16:y:2021:i:2:p:363-393 is not listed on IDEAS
    25. Christian Schlereth & Christine Eckert & Bernd Skiera, 2012. "Using discrete choice experiments to estimate willingness-to-pay intervals," Marketing Letters, Springer, vol. 23(3), pages 761-776, September.

    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:patien:v:17:y:2024:i:3:d:10.1007_s40271-023-00670-7. 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.