A disproportionality analysis of insulin glargine in the overall population and in pregnant women using the FDA adverse event reporting system (FAERS) database - Shaozhi Liu; Jun Xu; Zhongwen Yuan; Zhengrong Mei; Shengying Shi; Jinjin Yin; Yanhong Deng (PLoS ONE, 2025)
Background Insulin glargine (IG) is a commonly prescribed medication for diabetes management in clinical practice, however, there has yet to be a comprehensive systematic study examining its associated adverse events (AEs). In particular, due to the inherent limitations of clinical trials conducted during pregnancy, the safety profile of medications utilized in this period cannot be determined with absolute certainty. This study aims to evaluate the signals of AEs related to IG with in the overall population and among pregnant women, utilizing data from the FDA Adverse Event Reporting System (FAERS) database. Methods We employed standardized MedDRA queries to identify adverse event (AE) reports related to pregnancy. Through disproportionate analysis, we identified and analyzed AE reports from the FAERS database spanning January 2004 to June 2024. We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Conﬁdence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM) for signal detection. Further identification of signal strength based on the BCPNN method was conducted by categorizing signals into four levels based on the Information Component (IC) value and its 95% confidence interval: weak signals (0 < IC025 ≤ 1.5), moderate signals (1.5 < IC025 ≤ 3), and strong signals (IC025 > 3). Additionally, an analysis of the temporal distribution characteristics of AEs was performed. Results We obtained 70 strong or medium signals of AEs for IG in the overall population and 28 positive signals of AEs in pregnant women. In the overall population, the most significant signals included blood glucose abnormal (IC025 = 4.86), blood glucose fluctuation (IC025 = 4.69), blood glucose decreased (IC025 = 4.44), hypoglycaemic seizure (IC025 = 4.44) and hypoglycaemic unconsciousness (IC025 = 4.31). In pregnant women, hypoglycaemia (IC025 = 4.25) was detected as a strong signal, hypoglycaemia neonatal (IC025 = 2.96) as a medium signal, while ketoacidosis (IC025 = 0.76), decreased insulin requirement (IC025 = 0.24), and underweight (IC025 = 0.09) were identified as weak signals. The median time-to-onset of AEs was significantly longer in pregnant women compared to the overall population (186 days vs. 61 days). Conclusion This study has identified unexpected AE signals associated with IG in pregnant women. Our research provides valuable evidence for the clinical application of IG, offers real-world data to support safe medication practices during pregnancy, and establishes a foundation for further clinical investigations.