| 摘要: |
| 目的:挖掘美国食品药品监督管理局不良事件报告系统(FAERS)数据库,调研抗癫痫药物卢非酰胺、氯巴占、大麻二酚
的不良事件,为保障患者用药安全提供参考。方法:采用报告比值比(ROR)法和贝叶斯置信区间递进神经网络(BCPNN) 法对
FAERS 数据库中2018-2023 年上报的儿童抗癫痫药物不良事件进行挖掘分析。结果:抗癫痫药物不良事件好发于5~12 岁儿
童,男性患儿多于女性;神经系统不良事件是最突出的问题,痫性发作数量最多;关联强度:大麻二酚>氯巴占>卢非酰胺。本研
究意外地发现了新的信号,如肌张力减低、认知障碍、书写困难等。结论:本研究结果与临床观察结果一致,且发现了抗癫痫药
物神经系统不良事件的新信号,但需进一步前瞻性临床研究来证实和阐明抗癫痫药物与神经系统不良事件的关系。 |
| 关键词: 食品药品监督管理局不良事件报告系统数据库 卢非酰胺 大麻二酚 氯巴占 报告比值比 贝叶斯置信区间递进神经
网络 |
| DOI：doi:10.13407/j.cnki.jpp.1672-108X.2025.05.009 |
|
| 基金项目:基金项目:重庆市科卫联合医学科研项目,编号2022MSXM084。 |
|
| Safety Assessment of Antiepileptic Drugs Lufenamide, Clobazam and Cannabidiol in Children |
| Xie Jing1, Xiang Qiumeng2, Jia Qingyan2, Liu Limei2 |
| (1. Chongqing Dongnan Hospital, Chongqing 400000, China;
2. Chongqing Youyoubaobei Women and Children’s Hospital, Chongqing 401120, China) |
| Abstract: |
| Objective: To investigate the adverse events of antiepileptic drugs (lufenamide, clobazam, and cannabidiol) based on data
mining of the U. S. Food and Drug Administration Adverse Event Reporting System (FAERS) database, and to provide reference for the
safe medication for patients. Methods: The reporting odds ratio (ROR) and Bayesian confidence propagation neural network (BCPNN)
methods of proportional imbalance measurement were used to mine and analyze the adverse events of antiepileptic drugs in FAERS
database from 2018 to 2023. Results: Epilepsy drug adverse events were more common in children aged from 5 to 12 years, with more
males than females. Neurological adverse events were the most prominent problem, and epileptic seizures were the most frequent.
Association strength was cannabidiol > clobazam > lufeamide. Unexpectedly, new signals such as hypotonia, mental deficits, and writing
difficulties were identified. Conclusion: Results of the study are consistent with clinical observation, and a new signal of neurological
adverse events of antiepileptic drugs has been found, yet further prospective clinical studies are needed to confirm and clarify the
correlation between antiepileptic drugs and neurological adverse events. |
| Key words: Food and Drug Administration Adverse Event Reporting System database lufinamide cannabidiol clobazam reporting
odds ratio Bayesian confidence propagation neural network |
