Signal mining and risk analysis of olanzapine adverse events in the FAERS database

利用FAERS数据库对奥氮平不良事件进行信号挖掘和风险分析

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Abstract

OBJECTIVE: This study assessed the safety profile of olanzapine by analyzing adverse events reported in the U.S. Food and Drug Administration's Adverse Event Reporting System database, particularly focusing on newly identified risks. METHODS: The study involved olanzapine-related adverse events that occurred between January 1, 2004, and June 30, 2023. Four signal mining methods were used for a comprehensive analysis of the frequency and strength of adverse events, including the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and empirical Bayesian geometric mean. RESULTS: A total of 43,664 reports with olanzapine as the primary suspect drug were collected, and 776 preferred terms signals involving 27 system organ classes were identified. The main affected groups were females and individuals between 18 and 45 years of age. Psychiatric disorders and nervous system disorders were the most common adverse reactions. The analysis also revealed some adverse reactions not recorded in the manual, including cardiovascular risk, such as pancreatitis, increased chylomicron, hyperchylomicronemia, and myocardial reperfusion injury, as well as rare but serious adverse reactions like neuroleptic malignant syndrome and anosognosia. CONCLUSIONS: This study identified new cardiovascular risks associated with olanzapine, including pancreatitis and myocardial reperfusion injury, which require further investigation.

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