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碘造影剂不良事件信号数据挖掘与分析。

IF 3.2 4区 医学 Q2 PHARMACOLOGY & PHARMACY
Juntao Tan , Yue Yu , Yuxin He , Jiangyuan Zheng , Qingzhu Tan , Xiao Zhang , Chao Wan , Zhengyu Zhang , Xiaoxin Wu , Rui Tan
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引用次数: 0

摘要

背景:本研究旨在利用美国食品药品监督管理局(FDA)不良事件报告系统(FAERS)数据库,对碘化造影剂(ICM)相关不良事件进行挖掘和分析,探讨不良事件(ae)的特点,包括发生情况及ae与药物的相关性,为临床应用提供有价值的见解。方法:查询FAERS数据库,提取2004年第一季度至2023年第二季度的数据,收集5例ICMs为主要嫌疑的AE报告。采用报告优势比(ROR)、比例报告比(PRR)、贝叶斯置信传播神经网络(BCPNN)和经验贝叶斯几何平均(EBGM)对相关报告进行数据挖掘和分析,并使用标准化医学词典(MedDRA)查询(SMQ)进行系统分类。结果:FAERS共检索到11,155,106份AE报告,其中ioversol 2,412份,iohexol 2,001份,iodixanol 987份,iopamidol 1,154份,ioproide 3,835份。icm诱导的AE发生针对21个系统器官类别(soc)。同时保留了符合4种算法的329个显著歧化首选项(PTs)。结果显示,5种ICMs的中度和重度药物不良反应(ADR)信号主要集中在“呼吸、胸腔和纵隔疾病”、“一般疾病和给药部位情况”、“免疫系统疾病”和“皮肤和皮下组织疾病”。Ioversol (log2ROR = 1.21, Padj = 0.034)和ioproide (log2ROR = 1.32, Padj = 0.004)均与较高的显著不良反应信号发生率相关,即咽喉刺激,尤其是在女性中。此外,ioversol和ioproide还提示中毒性肾病(log2ROR = -2.47, Padj < 0.001)和多汗症(log2ROR = -1.22, Padj = 0.001)是显著的ADR信号,尤其是在男性中。结论:5种ICMs的AE分布一致,但具体的ADR信号特征存在差异,值得进一步考虑和探讨。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Mining and Analysis for Iodinated Contrast Media Adverse Event Signals Based on the Food and Drug Administration Adverse Event Reporting System Database

Background

The purpose of this study was to employ the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database to mine and analyze adverse events related to iodinated contrast media (ICM), explore the characteristics of adverse events (AEs) including their occurrence and correlation strength between AEs and drugs, and to provide valuable insights for clinical use.

Methods

The FAERS database was queried, data from Q1 of 2004 to Q2 of 2023 were extracted, and AE reports targeting 5 ICMs as the primary suspects were collected. Data mining and analysis were carried out on relevant reports using the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), while the standardized medical dictionary for regulatory activities (MedDRA) queries (SMQ) was used for systematic classification.

Results

A total of 11,155,106 AE reports were retrieved from FAERS, with 2,412 for ioversol, 2,001 for iohexol, 987 for iodixanol, 1,154 for iopamidol, and 3,835 for iopromide. ICM-induced AE occurrence targeted 21 system organ classes (SOCs). A total of 329 significant disproportionality Preferred terms (PTs) conforming to the 4 algorithms were simultaneously retained. The results revealed that the medium and strong adverse drug reaction (ADR) signals of the 5 ICMs largely focused on “respiratory, thoracic and mediastinal disorders,” “general disorders and administration site conditions,” “immune system disorders,” and “skin and subcutaneous tissue disorders.” Ioversol (log2ROR = 1.21, Padj = 0.034) and iopromide (log2ROR = 1.32, Padj = 0.004) were both correlated with a higher incidence of a significant ADR signal, namely throat irritation, particularly in females. In addition, ioversol and iopromide also suggested that toxic nephropathy (log2ROR = −2.47, Padj < 0.001) and hyperhidrosis (log2ROR = −1.22, Padj = 0.001) were significant ADR signals, especially in males, respectively.

Conclusions

While the AE distribution of the 5 ICMs was consistent, there were variations in specific ADR signal characteristics, warranting further consideration and exploration.
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来源期刊
Clinical therapeutics
Clinical therapeutics 医学-药学
CiteScore
6.00
自引率
3.10%
发文量
154
审稿时长
9 weeks
期刊介绍: Clinical Therapeutics provides peer-reviewed, rapid publication of recent developments in drug and other therapies as well as in diagnostics, pharmacoeconomics, health policy, treatment outcomes, and innovations in drug and biologics research. In addition Clinical Therapeutics features updates on specific topics collated by expert Topic Editors. Clinical Therapeutics is read by a large international audience of scientists and clinicians in a variety of research, academic, and clinical practice settings. Articles are indexed by all major biomedical abstracting databases.
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