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How Do Members of the Duchenne and Becker Muscular Dystrophy Community Perceive a Discrete-Choice Experiment Incorporating Uncertain Treatment Benefit? An Application of Research as an Event

Author

Listed:
  • John F. P. Bridges

    (The Johns Hopkins Bloomberg School of Public Health
    The Johns Hopkins Bloomberg School of Public Health)

  • Jui-Hua Tsai

    (The Johns Hopkins Bloomberg School of Public Health)

  • Ellen Janssen

    (The Johns Hopkins Bloomberg School of Public Health)

  • Norah L. Crossnohere

    (The Johns Hopkins Bloomberg School of Public Health)

  • Ryan Fischer

    (Parent Project Muscular Dystrophy)

  • Holly Peay

    (The Johns Hopkins Bloomberg School of Public Health
    Parent Project Muscular Dystrophy
    RTI International)

Abstract

Background Best–worst scaling methods have been used in several Duchenne and Becker muscular dystrophy (DBMD) studies to quantify patient and caregiver priorities and preferences and promote patient-focused drug development (PFDD). We sought to assess the extent to which different members of the DBMD community would accept a discrete-choice experiment (DCE) that incorporates uncertainty regarding individual-level benefit. Methods A community advisory board encouraged the development and testing of a DCE to further examine treatment preferences in DBMD and to facilitate the inclusion of a policy-relevant uncertainty attribute. The DCE assessed preferences across a primary outcome (muscle strength) and several risks (uncertainty regarding treatment benefit, kidney damage risk, and fracture risk). The single instrument was tested among adult patients, caregivers, and professionals at the national Parent Project Muscular Dystrophy annual meeting. The DCE was analyzed using conditional logit. Instrument acceptability was evaluated using a previously developed set of questions assessing ease of understanding and answering, and if answers reflected the respondents’ real preferences. We proposed a 75% agreement rate as a threshold of acceptability, and used a Z score to assess if this was met, exceeded, or rejected. Results A total of 161 people completed the survey including 9 patients, 87 caregivers, and 65 professionals. Patients reported high acceptability across all evaluation items (p values > 0.21). Caregivers and professionals exceeded the benchmark of acceptability on understanding and reflecting real preferences (p

Suggested Citation

  • John F. P. Bridges & Jui-Hua Tsai & Ellen Janssen & Norah L. Crossnohere & Ryan Fischer & Holly Peay, 2019. "How Do Members of the Duchenne and Becker Muscular Dystrophy Community Perceive a Discrete-Choice Experiment Incorporating Uncertain Treatment Benefit? An Application of Research as an Event," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 12(2), pages 247-257, April.
    • Handle: RePEc:spr:patien:v:12:y:2019:i:2:d:10.1007_s40271-018-0330-8
    DOI: 10.1007/s40271-018-0330-8
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    References listed on IDEAS

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    1. John Bridges & Elizabeth Kinter & Annette Schmeding & Ina Rudolph & Axel Mühlbacher, 2011. "Can Patients Diagnosed with Schizophrenia Complete Choice-Based Conjoint Analysis Tasks?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 4(4), pages 267-275, December.
    2. Mark Harrison & Dan Rigby & Caroline Vass & Terry Flynn & Jordan Louviere & Katherine Payne, 2014. "Risk as an Attribute in Discrete Choice Experiments: A Systematic Review of the Literature," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(2), pages 151-170, June.
    3. Jane Hall & Patricia Kenny & Madeleine King & Jordan Louviere & Rosalie Viney & Angela Yeoh, 2002. "Using stated preference discrete choice modelling to evaluate the introduction of varicella vaccination," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 457-465, July.
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