Abstract
BACKGROUND: Obinutuzumab is the first glycosylated type II anti-CD20 monoclonal antibody for the treatment of lymphocytic leukemia and follicular lymphoma. This research aimed to identify significant and unexpected adverse events (AEs) associated with obinutuzumab by utilizing data from the US Food and Drug Administration's Adverse Event Reporting System (FAERS) and the Japanese Adverse Drug Event Report (JADER) databases, with the intention of providing a reference for the safe and rational clinical use of the drug. RESEARCH DESIGN AND METHODS: The reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayesian geometric average (EBGM) were employed to analyze the AEs of obinutuzumab using the registration data from the FAERS and JADER databases spanning from 2013 to 2025. RESULTS: The study screened 7,868 and 1,584 AE reports related to obinutuzumab from the FAERS and JADER databases, respectively. These AEs involved 198 and 39 risk signals, respectively, and were associated with 16 and 8 system organ classes. In the analysis of the top 30 preferred terms, 19 and 15 risk signals in the FAERS and JADER databases, respectively, were not documented in the drug instruction. Moreover, when obinutuzumab is used for tumor indications, the frequency and signal strength of AEs related to infection and infusion-related reaction (IRR) are higher than those when it is used for non-tumor indications. CONCLUSION: The results of signal mining indicate that more attention should be paid to the risks of obinutuzumab-related AEs. Strengthening clinical medication monitoring is necessary to mitigate the impact of AEs on patients' prognosis and quality of life.