中国临床保健杂志2025，Vol.28Issue(6)：780-791,12.DOI:10.3969/J.issn.1672-6790.2025.06.011
基于美国食品药品监督管理局不良事件报告系统数据库的药源性睡眠障碍信号挖掘研究
Signal mining of drug-induced sleep disorder based on FAERS database
摘要
Abstract
Objective To identify drugs associated with increased risk of sleep disorders through mining and analyzing the FDA Adverse Event Reporting System(FAERS)database,thereby mitigating drug-induced sleep disturbances and improving clinical medication safety.Methods Reports of sleep disorder from the FAERS database between January 2004 to December 2024 were collected.Two disproportionality analysis methods,the Reporting Odds Ratio(ROR)and the Bayesian Confidence Propagation Neural Network,were employed to detect adverse reaction signals associated with drug-induced sleep disorders.Results A total of 131 174 sleep disorder-related reports were analyzed,identifying 233 drugs with positive signals.Among these,32 medications had sleep disorder risks not documented in their prescribing information.The top three most frequently reported drugs with positive signals were dupilumab(ROR=3.48),sodium oxybate(ROR=10.36),and varenicline(ROR=4.42).Conclusions Some medications are associated with drug-induced sleep disorders,particularly nervous system drugs.Various pharmacological agents,especially neuroactive drugs,correlate with medication-induced sleep disturbances.Clinical practitioners should evaluate drug-related somnolence/insomnia risks to optimize treatment strategies.关键词
睡眠异常/药物警戒性/药物相关性副作用和不良反应/数据挖掘Key words
Dyssomnias/Pharmacovigilance/Drug-related side effects and adverse reactions/Data mining引用本文复制引用
杨其亮,朱峰,周双,倪文骐,刘晓盈..基于美国食品药品监督管理局不良事件报告系统数据库的药源性睡眠障碍信号挖掘研究[J].中国临床保健杂志,2025,28(6):780-791,12.基金项目
中央保健科研项目(2024YB04) （2024YB04）
