Evidence map›Paper›PMID 30259384›Full record

ArticleThe patient2019

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 Bridges, Jui-Hua Tsai, Ellen Janssen, Norah L Crossnohere, Ryan Fischer, Holly Peay

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Article in The patient, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Valuing health and wellbeing using discrete choice experiment: exploring feasibility, design effect and international preference similarity.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
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  8. Diagnostic experiences of Duchenne families and their preferences for newborn screening: A mixed-methods study.American journal of medical genetics. Part C, Seminars in medical genetics · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

John F P BridgesDepartment of Health Policy and Management, The Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA.
Jui-Hua TsaiDepartment of Health Policy and Management, The Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA.
Ellen JanssenDepartment of Health Policy and Management, The Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA.
Norah L CrossnohereDepartment of Health, Behavior, and Society, The Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA. ncrossn1@jhu.edu.
Ryan FischerParent Project Muscular Dystrophy, 401 Hackensack Avenue, 9th Floor, Hackensack, NJ, 07601, USA.
Holly PeayDepartment of Health, Behavior, and Society, The Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St, Baltimore, MD, 21205, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBest-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.

methodsA 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.

resultsA 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).

conclusionsThis 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.

Indexed as

Choice BehaviorResearchUncertaintyAdolescentAdultFemaleHumansMaleMiddle AgedMuscular Dystrophy, DuchennePerceptionPolicyRisk AssessmentYoung Adult

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.