Glucagon-Like Peptide-1 Receptor Agonist Treatment Attributes Important to Injection-Experienced Patients with Type 2 Diabetes Mellitus: A Preference Study in Germany and the United Kingdom

Introduction: This study assessed the relative importance of treatment-related attributes in influencing patient preferences for glucagon-like peptide-1 receptor agonists (GLP-1RAs) among injection-experienced type 2 diabetes mellitus (T2DM) patients in Germany and the United Kingdom. Methods: T2DM patients experienced with injecting once-weekly (QW) exenatide or once-daily (QD) liraglutide completed an online discrete-choice experiment (DCE) survey. Patients chose between hypothetical blinded treatment profiles reflecting attributes of GLP-1RAs. The DCE survey included eight attributes: efficacy, side effects, device size, needle size, titration, injection preparation, long-term efficacy/safety, and dosing frequency. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using a conditional logit model indicating the likelihood of choosing a treatment with a given attribute level versus a reference attribute level. Results: 510 GLP-1RA injection-experienced patients completed the survey; 45.3% respondents were being treated with exenatide QW and 54.7% respondents were being treated with liraglutide QD. In terms of GLP-1RA attributes, patients indicated a preference for a treatment with greater efficacy (i.e., a 1.5-point improvement in HbA1c) (OR 2.58; 95% CI 2.37, 2.80; p<0.001), fewer side effects (OR 2.67; 95% CI 2.52, 2.82; p<0.001), once-weekly rather than once-daily administration (OR 2.26; 95% CI 2.13, 2.39; p<0.001), and the preparation required for a multi-use pen (OR 1.71; 95% CI 1.55, 1.88; p<0.001). Needle size, device size, and titration were not significant drivers of patient preference. Conclusions: Among GLP-1RA injection-experienced patients, key drivers of treatment preference for a hypothetical GLP-RA profile were side effects, efficacy, dosing frequency, and required preparation. Understanding patient preferences is important for optimizing treatment decision-making and improving treatment adherence.