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Decision Making About Disease-Modifying Treatments for Relapsing-Remitting Multiple Sclerosis: Stated Preferences and Real-World Choices

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Abstract

Background

People with relapsing-remitting multiple sclerosis can benefit from disease-modifying treatments (DMTs). Several DMTs are available that vary in their efficacy, side-effect profile and mode of administration.

Objective

We aimed to measure the preferences of people with relapsing-remitting multiple sclerosis for DMTs using a discrete choice experiment and to assess which stated preference attributes correlate with the attributes of the DMTs they take in the real world.

Methods

Discrete choice experiment attributes were developed from literature reviews, interviews and focus groups. In a discrete choice experiment, participants were shown two hypothetical DMTs, then chose whether they preferred one of the DMTs or no treatment. A mixed logit model was estimated from responses and individual-level estimates of participants’ preferences conditional on their discrete choice experiment choices calculated. Logit models were estimated with stated preferences predicting current real-world on-treatment status, DMT mode of administration and current DMT.

Results

A stated intrinsic preference for taking a DMT was correlated with currently taking a DMT, and stated preferences for mode of administration were correlated with the modes of administration of the DMTs participants were currently taking. Stated preferences for treatment effectiveness and adverse effects were not correlated with real-world behaviour.

Conclusions

There was variation in which discrete choice experiment attributes correlated with participants’ real-world DMT choices. This may indicate patient preferences for treatment efficacy/risk are not adequately taken account of in prescribing. Treatment guidelines must ensure they take into consideration patients’ preferences and improve communication around treatment efficacy/risk.

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Notes

  1. It is not possible to give a precise number, as because of an error, an unknown number of people with progressive MS were also invited. The MS Register has over 25,000 members; however, because of changes to data protection laws shortly before the survey launch, we could only invite those who explicitly consented to being contacted to complete external surveys.

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Author information

Authors and Affiliations

  1. Leeds Institute of Health Sciences, University of Leeds, Leeds, UK

    Edward J. D. Webb, David Meads & Hilary L. Bekker

  2. School of Law, University of Leeds, Leeds, UK

    Ieva Eskytė

  3. Leeds Teaching Hospitals NHS Trust, Leeds, UK

    Helen L. Ford

  4. The Research Centre for Patient Involvement, Central Denmark Region, Aarhus, Denmark

    Hilary L. Bekker

  5. Queen Square Multiple Sclerosis Centre, Department of Neuroinflammation, University College London, London, UK

    Jeremy Chataway

  6. Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK

    Jeremy Chataway

  7. Shift.ms, Leeds, UK

    George Pepper

  8. Centre for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland

    Joachim Marti

  9. Centre for Decision Research, Leeds University Business School, University of Leeds, Leeds, UK

    Yasmina Okan

  10. Department of Communication, Pompeu Fabra University, Barcelona, Spain

    Yasmina Okan

  11. Dental Translational and Clinical Research Unit, School of Dentistry, University of Leeds, Leeds, UK

    Sue H. Pavitt

  12. Blizard Institute (Neuroscience) Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK

    Klaus Schmierer

  13. Clinical Board Medicine (Neuroscience), The Royal London Hospital, Barts Health NHS Trust, London, UK

    Klaus Schmierer

  14. School of Sociology and Social Policy, University of Leeds, Leeds, UK

    Ana Manzano

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  1. Edward J. D. Webb
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Corresponding author

Correspondence to Edward J. D. Webb.

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Funding

This study was funded by the UK Multiple Sclerosis Society, Grant no. 30. The research was supported by the National Institute for Health Research (NIHR) infrastructure at Leeds. The views expressed are those of the author(s) and not necessarily those of the National Health Service, the NIHR or the Department of Health and Social Care. Yasmina Okan acknowledges support from a Population Research Fellowship awarded by Cancer Research UK (reference C57775/A22182). Jeremy Chataway is supported in part by the NIHR, University College London Hospitals, Biomedical Research Centre, London, UK. The funders have had no input into the study design, collection and analysis of data, the writing of the manuscript or the decision to submit it for publication.

Conflicts of interest/competing interests

Jeremy Chataway has received support from the Efficacy and Mechanism Evaluation Programme and Health Technology Assessment Programme (NIHR); UK Multiple Sclerosis Society and National Multiple Sclerosis Society; and the Rosetrees Trust. In the last 3 years, he has been a local principal investigator for trials in multiple sclerosis funded by Receptos, Novartis and Biogen Idec, and has received an investigator grant from Novartis outside this work. He has taken part in advisory boards/consultancy for Roche, Merck, MedDay, Biogen and Celgene. Klaus Schmierer has received support from the Efficacy and Mechanism Evaluation Programme and Health Technology Assessment Programme (NIHR); UK Multiple Sclerosis Society and National Multiple Sclerosis Society; consulting fees from Biogen, Merck, Novartis and Roche, and payments for lecturing activities from Biogen, Merck, Novartis, Roche, Teva, Neurology Academy and Medscape. Hilary L. Bekker provides guidance, based on her academic expertise in medical decision making, to health policy organisations, patient advocacy groups, health professionals and health scientists on research methods and techniques to develop and evaluate patient decision aids and shared decision-making interventions. Her time and expenses in attending meetings, carrying out evaluations and collaborating with other projects are remunerated. She does not gain financially from the outcomes or outputs of these collaborations. Helen Ford has received support from the Health Technology Assessment Programme (NIHR) and the UK MS Society. In the past 3 years, Helen Ford has been a local principal investigator for trials in multiple sclerosis funded by Biogen Idec, Novartis and Roche and has taken part in advisory boards and consultancy for Biogen, Merck, Novartis, Roche, Sanofi-Genzyme and Teva. Edward Webb, David Meads, Ieva Eskytė, George Pepper, Joachim Marti, Yasmina Okan, Sue Pavitt and Ana Manzano have no conflicts of interest that are directly relevant to the content of this article.

Ethics approval

Approval for this study was given by a National Health Service Research Ethics Committee. The MS Register has been approved by the South West Central Bristol National Research Ethics Service (16/SW/0194).

Consent to participate

All participants gave informed consent before completing the survey, as well as consent to merge their responses with data from the UK MS Register.

Consent for Publication

Patients gave informed consent regarding publishing anonymised data.

Availability of data and material

Discrete choice experiment data are not publicly available as consent was not obtained for this. They may be shared on a case-by-case basis if an application is made to Leeds Institute of Health Sciences and a formal data sharing agreement is entered into. For access to UK MS Register data, see https://ukmsregister.org/.

Code availability

Not applicable.

Author contributions

All authors conceived the study, defined the study aims and contributed to the survey design. EW and DM collected the data. EW conducted the statistical analysis and wrote the first draft of the manuscript, and all authors contributed to and approved the final version.

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Webb, E.J.D., Meads, D., Eskytė, I. et al. Decision Making About Disease-Modifying Treatments for Relapsing-Remitting Multiple Sclerosis: Stated Preferences and Real-World Choices. Patient 16, 457–471 (2023). https://doi.org/10.1007/s40271-023-00622-1

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