Drug-induced upper gastrointestinal bleeding: A real-world pharmacovigilance study

Abstract

Background Drug-induced upper gastrointestinal bleeding (UGIB) is a serious adverse event that deserves close attention. This study conducted a real-world pharmacovigilance research, aiming to enhance the understanding of drug safety and more effectively identify and prevent potential risks. Methods This study extracted data related to UGIB reported in the Food and Drug Administration Adverse Event Reporting System (FAERS) and Japanese Adverse Drug Event Report (JADER) databases from the first quarter of 2004 to the second quarter of 2024. We selected the top 50 drugs with higher frequency and conducted safety analyses using four signal detection methods: Reporting Odds Ratio, Proportional Reporting Ratio, Empirical Bayes Geometric Mean, and Bayesian Confidence Propagation Neural Network. Results Through data mining analysis, we found that the number of patients with UGIB reported was 62,941, including 57,414 in the FAERS and 5,527 in the JADER. It is particularly noteworthy that aspirin frequency and signal strength were among the top five in both databases. Rivaroxaban, warfarin, and pradaxa not only had the highest number of reports in the FAERS database but also showed highly in terms of their signal values. In the JADER database, clopidogrel, loxoprofen, apixaban, and bevacizumab had a higher number of reports, and it was also observed that esflurbiprofen/mentha oil and lornoxicam exhibited extremely high signal values. Meanwhile, meloxicam and prasugrel also had relatively high signal values. Conclusion This study conducted a pharmacovigilance analysis of drug-related UGIB by integrating and analyzing multiple adverse drug reaction databases. In both the FAERS and JADER databases, we not only identified some common risk-signaling drugs but also discovered database-specific risk-associated medications. In particular, this study performed a systematic quantitative risk assessment of the selected high-reporting-frequency drugs. This analysis not only deepened our understanding of drug risk profiles but also provided important reference evidence for clinical medication safety decision-making.