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Updated: Aug 31, 2026

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Preferences for Multiple Sclerosis Treatments: Using a Discrete-Choice Experiment to Examine Differences Across
Background:
The growing number of treatments for relapsing multiple sclerosis (MS) provides opportunities to consider patient preferences in treatment decisions.
Methods:
We designed a Web-based, discrete-choice experiment survey to analyze treatment preferences in patients with relapsing-remitting MS (RRMS). The survey presented hypothetical MS treatments defined by six attributes: risk of MS progression, time between relapses, risk of serious infection, treatment-related flu-like symptoms and gastrointestinal symptoms, and route and frequency of administration. Preference weights estimated with random-parameters logit were used to calculate importance scores and preference shares among three pairs of subsamples.
Results:
Patients with a self-reported physician diagnosis of RRMS (N = 301) completed the survey: 56% rated their disability level as normal or mild; 43% currently used a self-injectable treatment. Respondents with normal or mild disability levels placed greater weight on avoiding injections with flu-like symptoms and risk of progression, whereas patients with worse disability placed greater weight on reducing risk of progression and risk of serious infection. Patients taking injectables placed the most weight on risk of progression and risk of serious infection, whereas respondents not taking injectables placed the most weight on route and frequency of administration. Differences in preferences between subgroups were significant (P < .05). The presence of common adverse events associated with daily pills and injectables altered predicted preferences for route of administration.
Conclusions:
Preferences of patients with RRMS varied depending on current treatment and disability level, especially regarding mode of administration. Considering patient preferences for treatment features may lead to higher treatment satisfaction and adherence.
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