Literature DB >> 30259384

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.

John F P Bridges1,2, Jui-Hua Tsai1, Ellen Janssen1, Norah L Crossnohere3, Ryan Fischer4, Holly Peay2,4,5.   

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 < 0.001). Professionals met the benchmark (p = 0.08) for ease of answering, but caregivers did not (p < 0.01). DCE results demonstrated that all groups made meaningful trade-offs, with patients being less tolerant of risks than either caregivers or professionals (p < 0.001), and with no significant difference between caregivers and professionals (p = 0.46).
CONCLUSIONS: This study demonstrates the acceptable application of a single instrument across a multi-stakeholder population that used a complex preference method and included a policy-relevant uncertainty variable. Ease of answering was lowest among caregivers, but a post-hoc analysis revealed that it was most difficult for those with children under the age of 10, while those with older children met the threshold. The success of this study has laid the foundation for a global study of DBMD preferences using this method.

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Year:  2019        PMID: 30259384     DOI: 10.1007/s40271-018-0330-8

Source DB:  PubMed          Journal:  Patient        ISSN: 1178-1653            Impact factor:   3.883


  33 in total

1.  Conducting a Discrete-Choice Experiment Study Following Recommendations for Good Research Practices: An Application for Eliciting Patient Preferences for Diabetes Treatments.

Authors:  Ellen M Janssen; A Brett Hauber; John F P Bridges
Journal:  Value Health       Date:  2017-08-07       Impact factor: 5.725

2.  Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.

Authors:  John F P Bridges; A Brett Hauber; Deborah Marshall; Andrew Lloyd; Lisa A Prosser; Dean A Regier; F Reed Johnson; Josephine Mauskopf
Journal:  Value Health       Date:  2011-04-22       Impact factor: 5.725

Review 3.  Risk as an attribute in discrete choice experiments: a systematic review of the literature.

Authors:  Mark Harrison; Dan Rigby; Caroline Vass; Terry Flynn; Jordan Louviere; Katherine Payne
Journal:  Patient       Date:  2014       Impact factor: 3.883

Review 4.  Quantifying benefit-risk preferences for medical interventions: an overview of a growing empirical literature.

Authors:  A Brett Hauber; Angelyn O Fairchild; F Reed Johnson
Journal:  Appl Health Econ Health Policy       Date:  2013-08       Impact factor: 2.561

5.  Incorporating patient preferences into drug development and regulatory decision making: Results from a quantitative pilot study with cancer patients, carers, and regulators.

Authors:  D Postmus; M Mavris; H L Hillege; T Salmonson; B Ryll; A Plate; I Moulon; H-G Eichler; N Bere; F Pignatti
Journal:  Clin Pharmacol Ther       Date:  2016-02-17       Impact factor: 6.875

6.  Patient-centered benefit-risk assessment in duchenne muscular dystrophy.

Authors:  Ilene L Hollin; Holly L Peay; Susan D Apkon; John F P Bridges
Journal:  Muscle Nerve       Date:  2017-01-27       Impact factor: 3.217

7.  Caregiver preferences for emerging duchenne muscular dystrophy treatments: a comparison of best-worst scaling and conjoint analysis.

Authors:  Ilene L Hollin; Holly L Peay; John F P Bridges
Journal:  Patient       Date:  2015-02       Impact factor: 3.883

Review 8.  The treatment of hemophilia A: from protein replacement to AAV-mediated gene therapy.

Authors:  Shen Youjin; Yin Jun
Journal:  Biotechnol Lett       Date:  2008-11-02       Impact factor: 2.461

9.  Developing a Patient-Centered Benefit-Risk Survey: A Community-Engaged Process.

Authors:  Ilene L Hollin; Caroline Hanson; John F P Bridges; Holly Peay
Journal:  Value Health       Date:  2016 Sep - Oct       Impact factor: 5.725

10.  Developing an instrument to assess patient preferences for benefits and risks of treating acute myeloid leukemia to promote patient-focused drug development.

Authors:  Jaein Seo; B Douglas Smith; Elihu Estey; Ernest Voyard; Bernadette O' Donoghue; John F P Bridges
Journal:  Curr Med Res Opin       Date:  2018-04-27       Impact factor: 2.580

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  3 in total

1.  Analysis of Patient Preferences in Lung Cancer - Estimating Acceptable Tradeoffs Between Treatment Benefit and Side Effects.

Authors:  Ellen M Janssen; Sydney M Dy; Alexa S Meara; Peter J Kneuertz; Carolyn J Presley; John F P Bridges
Journal:  Patient Prefer Adherence       Date:  2020-06-03       Impact factor: 2.711

2.  Gene therapy as a potential therapeutic option for Duchenne muscular dystrophy: A qualitative preference study of patients and parents.

Authors:  Holly Landrum Peay; Ryan Fischer; Janice P Tzeng; Sharon E Hesterlee; Carl Morris; Amy Strong Martin; Colin Rensch; Edward Smith; Valeria Ricotti; Katherine Beaverson; Hannah Wand; Carol Mansfield
Journal:  PLoS One       Date:  2019-05-01       Impact factor: 3.240

3.  A Comparison of Caregiver and Patient Preferences for Treating Duchenne Muscular Dystrophy.

Authors:  Norah L Crossnohere; Ryan Fischer; Elizabeth Vroom; Patricia Furlong; John F P Bridges
Journal:  Patient       Date:  2022-03-04       Impact factor: 3.481

  3 in total

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