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基于FAERS数据库的真实世界数据对纳曲酮不良事件信号进行挖掘与不成比例性分析。

Mining and disproportionality analysis of adverse events signals for naltrexone based on real-world data from the FAERS database.

作者信息

Zeng Yaqi, Chen Zhe, Luo Yaan, Luo Jing, Shi Li, Zhou Xuhui

机构信息

Department of Psychiatry, The School of Clinical Medicine, Hunan University of Chinese Medicine, Changsha, Hunan, China.

Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.

出版信息

Expert Opin Drug Saf. 2025 Feb 2:1-8. doi: 10.1080/14740338.2025.2461200.

Abstract

BACKGROUND

This study aims to analyze adverse events (AEs) associated with naltrexone based on the FAERS database, providing a foundation for its safety monitoring.

RESEARCH DESIGN AND METHODS

Disproportionality analysis methods, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) algorithms, were employed to quantify signals of naltrexone-related .

RESULTS

AEs related to naltrexone from the first quarter of 2013 to the fourth quarter of 2023 were extracted from the FAERS database for detailed analysis. Among a total of 41,757,311 reports 28,745 were directly associated with naltrexone, involving 27 organ systems. We identified 110 for AEs at the preferred term (PT) level using disproportionality analysis, which included known such as agitation, depressed mood, sleep disorder, tremor, delirium, and decreased libido. Additionally, our findings suggested potential risks of restless legs syndrome, eosinophilic pneumonia, and otolithiasis, which were not mentioned in the drug's label, thereby supplementing the existing safety information.

CONCLUSIONS

The analysis of the FAERS database identified associated with naltrexone, contributing to the awareness of clinical practitioners and pharmacists regarding the drug-related risk signals. This awareness facilitates timely preventive and therapeutic measures, ensuring patient safety.

摘要

背景

本研究旨在基于美国食品药品监督管理局不良事件报告系统(FAERS)数据库分析与纳曲酮相关的不良事件(AE),为其安全性监测提供依据。

研究设计与方法

采用不成比例分析方法,包括报告比值比(ROR)、比例报告比(PRR)、贝叶斯置信传播神经网络(BCPNN)和多项目伽马泊松收缩器(MGPS)算法,对纳曲酮相关信号进行量化。

结果

从FAERS数据库中提取了2013年第一季度至2023年第四季度与纳曲酮相关的不良事件进行详细分析。在总共41757311份报告中,28745份与纳曲酮直接相关,涉及27个器官系统。我们使用不成比例分析在首选术语(PT)级别识别出110种不良事件,其中包括已知的如激动、情绪低落、睡眠障碍、震颤、谵妄和性欲减退等。此外,我们的研究结果表明不宁腿综合征、嗜酸性粒细胞性肺炎和耳石症存在潜在风险,而这些在药品标签中未提及,从而补充了现有的安全信息。

结论

对FAERS数据库的分析确定了与纳曲酮相关的不良事件,有助于临床医生和药剂师了解药物相关风险信号。这种认识有助于及时采取预防和治疗措施,确保患者安全。

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