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药物相关性卟啉病:一项药物警戒研究。

Drug-associated porphyria: a pharmacovigilance study.

机构信息

Department of Hematology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Pharmacy, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Orphanet J Rare Dis. 2024 Aug 1;19(1):286. doi: 10.1186/s13023-024-03294-8.

Abstract

BACKGROUND

The potentially fatal attacks experienced by porphyria carriers are triggered by various porphyrinogenic drugs. However, determining the safety of particular drugs is challenging.

METHODS

We retrospectively used the U.S. Food and Drug Administration's Adverse Event Reporting System (FAERS) to identify drugs associated with porphyria as an adverse event (AE) extracted from data from January 2004 to March 2022. The associated search terms included "Porphyria," "Porphyria screen," "Porphyria non-acute," "Porphyria acute," "Acquired porphyria," and "Pseudoporphyria." Signal mining analysis was performed to identify the association between drugs and AEs by four algorithms, namely the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker.

RESULTS

FAERS reported 1470 cases of porphyria-related AEs, and 406 drugs were screened after combining trade and generic names. All four algorithms identified 52 drugs with signals. The characteristics of all the reports and signaling drugs were analyzed.

CONCLUSIONS

This is the first report of drug-associated porphyria that provides critical information on drug porphyrogenicity, facilitating rational and evidence-based drug prescription and improving the accuracy of porphyrogenicity prediction based on model algorithms. Moreover, this study serves a reference for clinicians to ensure that porphyrinogenic drugs are not prescribed to carriers of porphyria genetic mutations.

摘要

背景

卟啉症携带者可能会经历致命的攻击,这些攻击是由各种卟啉原生成药物引发的。然而,确定特定药物的安全性具有挑战性。

方法

我们使用美国食品和药物管理局的不良事件报告系统(FAERS)回顾性地确定与卟啉症相关的药物,这些药物是从 2004 年 1 月至 2022 年 3 月的数据中提取的作为不良事件(AE)的卟啉症相关药物。相关的搜索词包括“卟啉症”、“卟啉症筛查”、“非急性卟啉症”、“急性卟啉症”、“获得性卟啉症”和“假性卟啉症”。通过报告比值比、比例报告比、贝叶斯置信传播神经网络和多项伽马泊松收缩器这四种算法,进行信号挖掘分析,以识别药物与 AE 之间的关联。

结果

FAERS 报告了 1470 例卟啉症相关 AE,结合贸易和通用名筛选后,共筛选出 406 种药物。所有四种算法都确定了 52 种具有信号的药物。分析了所有报告和信号药物的特征。

结论

这是首例关于药物相关性卟啉症的报告,提供了关于药物致卟啉性的关键信息,有助于合理和基于证据的药物处方,并提高基于模型算法的致卟啉性预测的准确性。此外,本研究为临床医生提供了参考,以确保不向卟啉症基因突变携带者开卟啉原生成药物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6b8/11295309/0ba2c34c10ae/13023_2024_3294_Fig1_HTML.jpg

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