Identification and Prioritization of Important Attributes of Disease-Modifying Drugs in Decision Making among Patients with Multiple Sclerosis: A Nominal Group Technique and Best-Worst Scaling.

Understanding the preferences of patients with multiple sclerosis (MS) for disease-modifying drugs and involving these patients in clinical decision making can improve the concordance between medical decisions and patient values and may, subsequently, improve adherence to disease-modifying drugs. This study aims first to identify which characteristics-or attributes-of disease-modifying drugs influence patients´ decisions about these treatments and second to quantify the attributes' relative importance among patients.First, three focus groups of relapsing-remitting MS patients were formed to compile a preliminary list of attributes using a nominal group technique. Based on this qualitative research, a survey with several choice tasks (best-worst scaling) was developed to prioritize attributes, asking a larger patient group to choose the most and least important attributes. The attributes' mean relative importance scores (RIS) were calculated.Nineteen patients reported 34 attributes during the focus groups and 185 patients evaluated the importance of the attributes in the survey. The effect on disease progression received the highest RIS (RIS = 9.64, 95% confidence interval: [9.48-9.81]), followed by quality of life (RIS = 9.21 [9.00-9.42]), relapse rate (RIS = 7.76 [7.39-8.13]), severity of side effects (RIS = 7.63 [7.33-7.94]) and relapse severity (RIS = 7.39 [7.06-7.73]). Subgroup analyses showed heterogeneity in preference of patients. For example, side effect-related attributes were statistically more important for patients who had no experience in using disease-modifying drugs compared to experienced patients (p < .001).This study shows that, on average, patients valued effectiveness and unwanted effects as most important. Clinicians should be aware of the average preferences but also that attributes of disease-modifying drugs are valued differently by different patients. Person-centred clinical decision making would be needed and requires eliciting individual preferences