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通过食品药品监督管理局不良事件报告系统评估药物戒断综合征风险：一项全面的不成比例性分析。

Evaluating drug withdrawal syndrome risks through food and drug administration adverse event reporting system: a comprehensive disproportionality analysis.

作者信息

Zhang Zheng, Yang Qianzhi, Chen Minghao, Yang Wah, Wang Yuping

机构信息

Department of Pharmacy, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.

Department of Metabolic and Bariatric Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China.

出版信息

Front Pharmacol. 2024 Jul 10;15:1385651. doi: 10.3389/fphar.2024.1385651. eCollection 2024.

DOI:10.3389/fphar.2024.1385651
PMID:39050751
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11266151/
Abstract

OBJECTIVE

The study aims to identify the drugs associated with drug withdrawal syndrome in the Food and Drug Administration Adverse Event Reporting System (FAERS) and estimate their risks of causing withdrawal syndrome.

METHODS

All the data were collected from FAERS from the first quarter of 2004 to the third quarter of 2023. Disproportionality analyses of odds ratio (ROR) and proportional reported ratio were conducted to identify potential adverse effects signal of drug withdrawal syndrome.

RESULTS

A total of 94,370 reports related to withdrawal syndrome from the data. The top 50 drugs with most frequency reported were analyzed, and 29 exhibited a positive signal based on the number of reports. The top three categories of drugs with positive signals included opioids, antidepressant drugs and antianxiety drugs. Other classifications included opioid antagonist, muscle relaxant, antiepileptic drugs, analgesics, hypnotic sedative drugs and antipsychotic drugs.

CONCLUSION

Our analysis of FAERS data yielded a comprehensive list of drugs associated with withdrawal syndrome. This information is vital for healthcare professionals, including doctors and pharmacists, as it aids in better recognition and management of withdrawal symptoms in patients undergoing treatment with these medications.

摘要

目的

本研究旨在识别美国食品药品监督管理局不良事件报告系统（FAERS）中与药物戒断综合征相关的药物，并评估其引发戒断综合征的风险。

方法

所有数据均收集自FAERS在2004年第一季度至2023年第三季度期间的数据。进行比值比（ROR）的不成比例分析和比例报告比分析，以识别药物戒断综合征的潜在不良反应信号。

结果

数据中共有94370份与戒断综合征相关的报告。对报告频率最高的前50种药物进行了分析，其中29种基于报告数量显示出阳性信号。出现阳性信号的前三类药物包括阿片类药物、抗抑郁药和抗焦虑药。其他分类包括阿片类拮抗剂、肌肉松弛剂、抗癫痫药、镇痛药、催眠镇静药和抗精神病药。

结论

我们对FAERS数据的分析得出了一份与戒断综合征相关的药物综合清单。这些信息对包括医生和药剂师在内的医疗专业人员至关重要，因为它有助于更好地识别和管理使用这些药物进行治疗的患者的戒断症状。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/dcba298d9e55/fphar-15-1385651-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/914a95b3de8a/fphar-15-1385651-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/9e7db7bc1767/fphar-15-1385651-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/70df34dde8a4/fphar-15-1385651-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/8cc499dbadaa/fphar-15-1385651-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/dcba298d9e55/fphar-15-1385651-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/914a95b3de8a/fphar-15-1385651-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/9e7db7bc1767/fphar-15-1385651-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/70df34dde8a4/fphar-15-1385651-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/8cc499dbadaa/fphar-15-1385651-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65a1/11266151/dcba298d9e55/fphar-15-1385651-g005.jpg

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