Data mining study on adverse events of tirzepatide based on FAERS database
Yan Huo, Minghua Ma, Xiaolan Liao
Abstract
BACKGROUND: Tirzepatide is a novel dual gastric inhibitory polypeptide (GIP) and glucagon-like peptide-1 receptor agonist (GLP-1 RA) for type 2 diabetes or obesity. To explore the safety profile of tirzepatide in real-world clinical applications. RESEARCH DESIGN AND METHODS: A retrospective analysis of adverse events (AEs) reports associated with tirzepatide was conducted from the second quarter of 2022 through the fourth quarter of 2023, utilizing the FDA Adverse Event Reporting System (FAERS) database. Signal mining utilized the reporting odds ratio (ROR) method, and onset time was analyzed utilizing the Weibull Shape Parameter (WSP). RESULTS: We identified 25,215 AE reports related to tirzepatide, predominantly in the 65 to 85 age group. Four positive signals were found at the system organ classes level. Additionally,109 AEs at the preferred terms level with positive signals were indicated. Included among these are novel signals, such as the presence of thyroid mass, medullary thyroid carcinoma, and conditions affecting the reproductive system and breast. Most AEs occurred within the first 30 days. The WSP was 0.66, indicating a propensity for early failure type. CONCLUSIONS: This study identified several novel AE signals for tirzepatide, highlighting the need for careful monitoring, especially in the early stages of treatment.