title: Quantitative analysis of multiple sclerosis patients' preferences for drug treatment: a best-worst scaling study.
abstract: BACKGROUND
  With recent developments in drug therapy for multiple sclerosis (MS), new treatment options have become available presenting patients with complex treatment decisions.
  
  
  OBJECTIVE
  The objective of this study was to elicit patients' preferences for different attributes of MS drug therapy.
  
  
  METHODS
  A 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.
  
  
  RESULTS
  A 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.
  
  
  CONCLUSIONS
  This 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.
authors.affiliation: Faculty of Pharmaceutical Sciences, University of British Columbia, 2405 Wesbrook Mall, Vancouver, BC, Canada V6T 1Z3.
authors.forename: Larry D
authors.initials: LD
authors.lastname: Lynd
authors.affiliation: Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
authors.forename: Anthony
authors.initials: A
authors.lastname: Traboulsee
authors.affiliation: School of Pharmacy, Memorial University of Newfoundland, St John's, Canada.
authors.forename: Carlo A
authors.initials: CA
authors.lastname: Marra
authors.affiliation: Sunnybrook Research Institute, Toronto, Canada.
authors.forename: Nicole
authors.initials: N
authors.lastname: Mittmann
authors.affiliation: College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Canada.
authors.forename: Charity
authors.initials: C
authors.lastname: Evans
authors.affiliation: Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Canada.
authors.forename: Kathy H
authors.initials: KH
authors.lastname: Li
authors.affiliation: Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Canada.
authors.forename: Melanie
authors.initials: M
authors.lastname: Carter
authors.affiliation: Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Canada.
authors.forename: Celestin
authors.initials: C
authors.lastname: Hategekimana
keywords: best–worst scaling; multiple sclerosis; patient preference; risk to benefit tradeoff