Optimizing Selection of Biologics in Inflammatory Bowel Disease: Development of an Online Patient Decision Aid Using Conjoint Analysis

• Published in: The American journal of gastroenterology Vol. 113; no. 1; pp. 58 - 71
• Main Authors: Almario, Christopher V, Keller, Michelle S, Chen, Michelle, Lasch, Karen, Ursos, Lyann, Shklovskaya, Julia, Melmed, Gil Y, Spiegel, Brennan M R
• Format: Journal Article
• Language: English
• Published: United States Wolters Kluwer Health Medical Research, Lippincott Williams & Wilkins 01.01.2018
• Subjects: Conjoint analysis; Decision making; Gastroenterology; Inflammatory bowel disease; Patients
• ISSN: 0002-9270; 1572-0241
• DOI: 10.1038/ajg.2017.470

Recent drug approvals have increased the availability of biologic therapies for inflammatory bowel disease (IBD), making it difficult for patients with ulcerative colitis (UC) and Crohn's disease (CD) to navigate treatment options. Here we developed a conjoint analysis to examine patient decision-making surrounding biologic medicines for IBD. We used the results to create an online patient decision aid that generates a unique "preferences report" for each patient to assist with shared decision-making with their provider. We administered an adaptive choice-based conjoint survey to IBD patients that quantifies the relative importance of biologic attributes (e.g., efficacy, side effect profile, mode of administration, and mechanism of action) in decision making. The conjoint software determined individual patient preferences by calculating part-worth utilities for each attribute. We conducted regression analyses to determine if demographic and disease characteristics (e.g., type of IBD and severity) predicted how patients made decisions. 640 patients completed the survey (UC=304; CD=336). In regression analyses, demographics and IBD characteristics did not predict individual patient preferences; the main exception was IBD type. When compared to UC, CD patients were more likely to report side effect profile as most important (odds ratio (OR) 1.63, 95% confidence interval (CI) 1.16-2.30). Conversely, those with UC were more likely to value therapeutic efficacy (OR 1.41, 95% CI 1.01-2.00). Biologic decision-making is highly personalized; demographic and disease characteristics poorly predict individual preferences, indicating that IBD patients are unique and difficult to statistically categorize. The online decision tool resulting from this study (www.ibdandme.org) may be used by patients to support shared decision-making and optimize personalized biologic selection with their provider.