Early Signal Detection in GLP-1 Receptor Agonists in Spain: A Comparative Bayesian Disproportionality Analysis in 2024 and 2025

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are increasingly prescribed for type 2 diabetes mellitus and obesity. Their expanding use, including off-label indications, raises ongoing concerns regarding their evolving safety profiles. Objective: To identify and compare early positive safety signals associated with GLP-1 RAs in Spain during 2024 and 2025 using a Bayesian disproportionality approach adapted from the WHO-Uppsala Monitoring Centre. Methods: Spontaneous adverse drug reaction (ADR) reports submitted to the Spanish Pharmacovigilance System and involving GLP-1 RAs (ATC A10BJ) were analyzed. Reports up to June 2024 and June 2025 were included. A Bayesian Confidence Propagation Neural Network (BCPNN)-based model was used to estimate signal strength. Positive signals were defined as those with a false discovery rate (FDR) < 0.05 and relative risk (RR) ≥ 1. Signals were classified as new, reinforced, diminished, unchanged, or disappeared between the two years. Results: We analyzed 5,322 reports in 2024 and 6,746 in 2025. New signals identified in 2025 included intestinal obstruction (dulaglutide), acute pancreatitis (exenatide), and urticaria at the injection site (liraglutide). Several previously identified signals diminished or disappeared, suggesting dynamic changes in GLP-1 RA risk profiles. Conclusions: This comparative Bayesian pharmacovigilance analysis highlights the evolving safety landscape of GLP-1 RAs. Early signal detection can inform timely regulatory interventions and support safer clinical use.