Postmarketing Safety Signals and Medication‐Use Risks of GLP ‐1‐Based Therapies in Diabetes and Obesity: A Multi‐Source Pharmacovigilance and Regulatory Evidence‐Mapping Study
Authors' conclusion
Multi-source pharmacovigilance can improve interpretation of GLP-1 postmarketing safety evidence in diabetes and obesity care.
Study context
- Population
- GLP-1 primary-suspect case-product records in FDA Adverse Event Reporting System (FAERS), 2021Q1 through 2026Q1, in diabetes and obesity care
- Participants
- 243,114 case-product records
- Comparison
- Tirzepatide vs Semaglutide vs Dulaglutide vs Liraglutide vs Exenatide vs Lixisenatide
- Tirzepatiden = 133,100
- Semaglutiden = 55,619
- Dulaglutiden = 38,406
- Outcome
- Postmarketing safety signals and medication-use risks
Methodological detailsmulti-source, FAERS disproportionality analysis (reporting odds ratios, proportional reporting ratios, approximate Information Component), regulatory evidence-mapping
- Multi-source
- FAERS disproportionality analysis (reporting odds ratios, proportional reporting ratios, approximate Information Component)
- Regulatory evidence-mapping
Main finding
As reported in the abstract
- Frequently reported terms: incorrect dose administered, nausea, injection-site pain, diarrhoea, vomiting, off-label use, extra dose administered
- Prioritised domains: gastrointestinal intolerance, medication-use/device events, impaired gastric emptying, pancreatobiliary events, renal/dehydration events, hypoglycaemia
- Canada Vigilance and FDA labelling/SrLC mapping showed descriptive visibility for most major domains; medication-use terms reflected use-process rather than conventional adverse-drug-reaction issues
- Within 8 995 547 background reports
- No data source used to estimate incidence, comparative risk or causality
Original publication
Postmarketing Safety Signals and Medication‐Use Risks of GLP ‐1‐Based Therapies in Diabetes and Obesity: A Multi‐Source Pharmacovigilance and Regulatory Evidence‐Mapping Study. Diabetes Obes Metab. Published 3 September 2026. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →