Postmarketing Safety Signals and Medication-Use Risks of GLP-1-Based Therapies in Diabetes and Obesity: A...

To characterise postmarketing safety signals and medication-use risks associated with GLP-1 receptor agonists and the GIP/GLP-1 co-agonist tirzepatide in diabetes and obesity care using an integrated pharmacovigilance, utilisation-context, regulatory, and external-consistency framework.

FDA Adverse Event Reporting System (FAERS) data from 2021Q1 through 2026Q1 were processed using deleted-case exclusion, latest-case-version retention, and case-product deduplication with analysis at the GLP-1 primary-suspect case-product level. Primary-suspect records for semaglutide, tirzepatide, dulaglutide, liraglutide, exenatide, and lixisenatide were analysed using reporting odds ratios, proportional reporting ratios, and an approximate Information Component. Medicaid utilisation data, FDA labelling/Safety-Related Labelling Changes resources, FDA shortage and compounded-product communications, and Canada Vigilance reports provided contextual interpretation; no data source was used to estimate incidence, comparative risk, or causality.

The final FAERS analysis set included 243 114 GLP-1 primary-suspect case-product records within 8 995 547 background reports. Tirzepatide accounted for 133 100 records, followed by semaglutide (55619) and dulaglutide (38406). Frequently reported terms included incorrect dose administered, nausea, injection-site pain, diarrhoea, vomiting, off-label use, and extra dose administered. Prioritised domains included gastrointestinal intolerance, medication-use/device events, impaired gastric emptying, pancreatobiliary events, renal/dehydration events, and hypoglycaemia. Canada Vigilance and FDA labelling/SrLC mapping showed descriptive visibility for most major domains, while medication-use terms reflected use-process rather than conventional adverse-drug-reaction issues.

Multi-source pharmacovigilance can improve interpretation of GLP-1 postmarketing safety evidence in diabetes and obesity care. Findings should be interpreted as signal-prioritisation and medication-safety evidence, not as incidence, proof of causality, or population-level comparative risk, given the limited clinical interpretability of spontaneous-reporting data.