OBJECTIVES: To determine patients’ preferences for sodium-glucose cotransporter 2 inhibitors (SGLT-2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs).

METHODS: A cross-sectional, web-based discrete choice experiment (DCE) was conducted among U.S. adults with self-reported type 2 diabetes. A Bayesian efficient design was used to generate four blocks of nine choice sets. Each choice set contained two hypothetical SGLT-2i and GLP-1 RA alternatives described by six attributes—the administration route and frequency, the chance of reaching target A1C in six months, the percentage reduction in the risk of major adverse cardiovascular events (MACE), the chance of gastrointestinal side effects, the chance of genital infection, and monthly out-of-pocket cost—and an opt-out alternative. A total of 176 patients were asked to choose one alternative in each choice set of a block. Mixed logit (ML) and latent class (LC) models were used to examine patients’ preferences and preference heterogeneity.

RESULTS: Most patients were female (54.6%) and Caucasian (86.9%) with an average age of 60 years. The ML model indicated that all attributes were significantly associated with the preferences for the SGLT-2is and GLP-1 RAs in the expected direction and captured significant preference heterogeneity for all attributes. The best LC model revealed two patient classes. All attributes were significantly important for patients in class 1 (48.1%), while all attributes, except the chance of genital infection, were significant for patients in class 2 (51.9%). The patients in class 1 tended to be older and have more comorbidities.

CONCLUSIONS: The administration route and frequency, the chance of reaching target A1C, the risk reduction of MACE, the chance of gastrointestinal side effects, the chance of genital infection, and monthly out-of-pocket cost were significantly important to patients when choosing SGLT-2i and GLP-1 RA treatments. Significant preference heterogeneity among patients was observed.