Objective: To evaluate and compare patient and neurologist preferences for relapsing-remitting multiple sclerosis (RRMS) treatments with respect to benefits and risks associated with common and novel disease-modifying therapies, including brain volume loss (BVL).

Methods: Patients with non-highly-active RRMS and neurologists in the United Kingdom completed an online cross-sectional survey. Patients completed one discrete choice experiment (DCE) exercise and providers completed two, one focusing on treatment for non-highly-active RRMS and another focused on highly active RRMS. Respondents chose between two treatment profiles that varied on seven attributes identified in qualitative research: 2 year disability progression; 1 year relapse rate; rate of BVL; and risks of gastrointestinal symptoms, flu-like symptoms, infection and life-threatening event. Bayesian modeling was used to estimate attribute-level weighted preferences.

Results: Patients ( = 144) prioritized slowing the rate of BVL, followed by reducing risk of infection, rate of 2 year disability progression and 1 year relapse rate. For non-highly-active patients, neurologists ( = 101) prioritized slowing the rate of BVL, followed by reducing 2 year disability progression, risk of infection and 1 year relapse rate. For highly active patients, neurologists prioritized lowering the 1 year relapse rate, followed by slowing the rate of BVL and 2 year disability progression. In all three DCEs, rate of BVL was approximately twice as important as reducing the risks of flu-like symptoms, gastrointestinal symptoms and life-threatening event.

Conclusions: This study highlights similarities in treatment preferences for non-highly-active RRMS among patients and neurologists and differences in neurologists' preferences for treating non-highly-active vs. highly active RRMS. This research identifies BVL as a treatment outcome that should be discussed when physicians engage in shared decision-making with patients.

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http://dx.doi.org/10.1080/03007995.2021.1940911DOI Listing

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