Assessing Patient Decision-Making on Biologic and Small-Molecule Therapies in Inflammatory Bowel Diseases: Insights From a Conjoint Analysis in the United States, Canada, and the United Kingdom. Issue 10 (10th December 2020) - Patel, Devin B; van Deen, Welmoed K; Almario, Christopher V; Khalil, Carine; Warui, Esther; Bonthala, Nirupama; Melmed, Gil Y; Spiegel, Brennan M R
Abstract: Background: Recent drug approvals have increased the number of therapies available for inflammatory bowel disease (IBD), making it difficult for patients to navigate available treatment options. We examined patient decision-making surrounding biologic and small-molecule therapies in an international cohort of patients from the United States, Canada, and the United Kingdom using conjoint analysis (CA), a form of tradeoff analysis examining how respondents make complex decisions. Methods: We performed a CA survey that quantified the relative importance of therapy attributes (eg, efficacy, adverse effects) in decision-making. Patients with IBD were recruited from the general population and through specialty IBD clinics. We used a hierarchical Bayes analysis to model individual patients' preferences and compared the relative importance of medication attributes between countries and practice settings. Using a series of multivariable linear regression models, we assessed whether demographic and clinical characteristics (eg, IBD subtype, severity) predicted how patients made decisions. Results: Overall, 1077 patients in 3 countries completed the survey. No differences in the relative importance of medication attributes were observed between the 3 countries' general IBD populations. However, efficacy was more important for patients in the US-based IBD specialty care cohort than for the general IBD population (29% and 23% importance, respectively; P < 0.0001). A few demographic and clinical characteristics were associated with small changes in individual preferences. Conclusions: In this large international CA study, patients prioritized efficacy as the most important therapeutic attribute. Decision-making seemed to be highly personalized in that therapeutic preferences were hard to predict based on patient characteristics.