ArticleTherapeutic advances in neurological disorders2016
Quantitative analysis of multiple sclerosis patients' preferences for drug treatment: a best-worst scaling study.
Article in Therapeutic advances in neurological disorders, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
19 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Understanding Patient Preferences for Medication Process Attributes: A Systematic Literature Review.The patient · 2026Pooled it
- A Systematic Review of Discrete-Choice Experiments and Conjoint Analysis Studies in People with Multiple Sclerosis.The patient · 2018Pooled it
- Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.PharmacoEconomics · 2018Pooled it
- Patient Preferences for Self-Injectable Preventive Treatment for Migraine: A Multi-country Discrete Choice Experiment.Neurology and therapy · 2025Article
- Article
- A Best-Worst Scaling Study of the General Population's Preferences for Activities in Living Arrangements for Persons With Dementia.The patient · 2024Article
- Patient-based benefit-risk assessment of medicines: development, refinement, and validation of a content search strategy to retrieve relevant studies.Journal of the Medical Library Association : JMLA · 2022Article
- Exploring the Cost Effectiveness of Shared Decision Making for Choosing between Disease-Modifying Drugs for Relapsing-Remitting Multiple Sclerosis in the Netherlands: A State Transition Model.Medical decision making : an international journal of the Society for Medical Decision Making · 2020Article
- The Impact of Reproductive Issues on Preferences of Women with Relapsing Multiple Sclerosis for Disease-Modifying Treatments.The patient · 2020Article
- Development and usability testing of a patient decision aid for newly diagnosed relapsing multiple sclerosis patients.BMC neurology · 2019Article
- Comparison of preferences of healthcare professionals and MS patients for attributes of disease-modifying drugs: A best-worst scaling.Health expectations : an international journal of public participation in health care and health policy · 2018Article
- Factors Associated with Patient Preferences for Disease-Modifying Therapies in Multiple Sclerosis.Journal of managed care & specialty pharmacy · 2017Article
- Observational
- Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study.Patient preference and adherence · 2017Article
- Preliminary testing of a patient decision aid for patients with relapsing-remitting multiple sclerosis.Multiple sclerosis journal - experimental, translational and clinicalArticle
- Patient and physician preferences for multiple sclerosis treatments in Germany: A discrete-choice experiment study.Multiple sclerosis journal - experimental, translational and clinicalArticle
- Association of Unemployment and Informal Care with Stigma in Multiple Sclerosis: Evidence from the Survey on Living with Neurological Conditions in Canada.International journal of MS careArticle
- Perspectives of Patients with Multiple Sclerosis on Drug Treatment: A Qualitative Study.International journal of MS careArticle
- Factors associated with time from first-symptoms to diagnosis and treatment initiation of Multiple Sclerosis in Switzerland.Multiple sclerosis journal - experimental, translational and clinicalArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith recent developments in drug therapy for multiple sclerosis (MS), new treatment options have become available presenting patients with complex treatment decisions.
objectivesThe objective of this study was to elicit patients' preferences for different attributes of MS drug therapy.
methodsA representative sample of patients with MS across Canada (n=189) participated in a best-worst scaling study to quantify preferences for different attributes of MS drug therapy, including delaying progression, improving symptoms, preventing relapse, minor side effects, rare but serious adverse events (SAEs), and route of administration. Conditional logit models were fitted to estimate the relative importance of each attribute in influencing patients' preferences.
resultsA latent-class analysis revealed heterogeneity of preferences across respondents, with preferences differing across five classes. The most important attributes of drug therapy were the avoidance of SAEs for three classes and the improvement of symptoms for two other classes. Only a smaller group of patients demonstrated a specific preference for avoiding SAEs, and route of administration.
conclusionThis study shows that preferences for drug therapy among patients with MS are different, some of which can be explained by experiences with their disease and treatment. These findings can help to inform the focus of interactions that healthcare practitioners have with patients with MS, as well as further drug development.
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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.