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使用两个大型数据库分析抗胆碱能不良反应:美国食品和药物管理局不良事件报告系统数据库和日本药物不良反应报告数据库。

Analysis of anticholinergic adverse effects using two large databases: The US Food and Drug Administration Adverse Event Reporting System database and the Japanese Adverse Drug Event Report database.

机构信息

The Office of Institutional Research, Meiji Pharmaceutical University, Kiyose, Tokyo, Japan.

Division of Clinical Pharmacy, Department of Pediatric Pharmaceutical Sciences, Education and Research Center for Pharmacy, Meiji Pharmaceutical University, Kiyose, Tokyo, Japan.

出版信息

PLoS One. 2021 Dec 2;16(12):e0260980. doi: 10.1371/journal.pone.0260980. eCollection 2021.

Abstract

INTRODUCTION

Anticholinergic adverse effects (AEs) are a problem for elderly people. This study aimed to answer the following questions. First, is an analysis of anticholinergic AEs using spontaneous adverse drug event databases possible? Second, what is the main drug suspected of inducing anticholinergic AEs in the databases? Third, do database differences yield different results?

METHODS

We used two databases: the US Food and Drug Administration Adverse Event Reporting System database (FAERS) and the Japanese Adverse Drug Event Report database (JADER) recorded from 2004 to 2020. We defined three types of anticholinergic AEs: central nervous system (CNS) AEs, peripheral nervous system (PNS) AEs, and a combination of these AEs. We counted the number of cases and evaluated the ratio of drug-anticholinergic AE pairs between FAERS and JADER. We computed reporting odds ratios (RORs) and assessed the drugs using Beers Criteria®.

RESULTS

Constipation was the most reported AE in FAERS. The ratio of drug-anticholinergic AE pairs was statistically significantly larger in FAERS than JADER. Overactive bladder agents were suspected drugs common to both databases. Other drugs differed between the two databases. CNS AEs were associated with antidementia drugs in FAERS and opioids in JADER. In the assessment using Beers Criteria®, signals were detected for almost all drugs. Between the two databases, a significantly higher positive correlation was observed for PNS AEs (correlation coefficient 0.85, P = 0.0001). The ROR was significantly greater in JADER.

CONCLUSIONS

There are many methods to investigate AEs. This study shows that the analysis of anticholinergic AEs using spontaneous adverse drug event databases is possible. From this analysis, various suspected drugs were detected. In particular, FAERS had many cases. The differences in the results between the two databases may reflect differences in the reporting countries. Further study of the relationship between drugs and CNS AEs should be conducted.

摘要

简介

抗胆碱能不良反应(AEs)是老年人面临的一个问题。本研究旨在回答以下问题。首先,使用自发药物不良事件数据库分析抗胆碱能 AEs 是否可行?其次,数据库中哪些药物最有可能引起抗胆碱能 AEs?第三,数据库的差异是否会产生不同的结果?

方法

我们使用了两个数据库:美国食品和药物管理局不良事件报告系统数据库(FAERS)和日本药物不良事件报告数据库(JADER),记录时间为 2004 年至 2020 年。我们定义了三种类型的抗胆碱能 AEs:中枢神经系统(CNS)AEs、周围神经系统(PNS)AEs 以及这些 AEs 的组合。我们统计了病例数量,并评估了 FAERS 和 JADER 中药物-抗胆碱能 AE 对的比例。我们计算了报告比值比(ROR),并使用 Beers 标准®评估了这些药物。

结果

在 FAERS 中,便秘是报告最多的 AE。FAERS 中药物-抗胆碱能 AE 对的比例明显大于 JADER。两种数据库中都怀疑有治疗膀胱过度活动的药物是可疑药物。其他药物在两个数据库中有所不同。在 FAERS 中,CNS AEs 与抗痴呆药物相关,而在 JADER 中则与阿片类药物相关。在使用 Beers 标准®进行评估时,几乎所有药物都检测到了信号。在两个数据库之间,PNS AEs 的正相关性显著更高(相关系数 0.85,P=0.0001)。JADER 中的 ROR 明显更大。

结论

有许多方法可以研究 AEs。本研究表明,使用自发药物不良事件数据库分析抗胆碱能 AEs 是可行的。通过这项分析,发现了许多可疑药物。特别是,FAERS 中包含了大量病例。两个数据库之间结果的差异可能反映了报告国家之间的差异。应该进一步研究药物与 CNS AEs 之间的关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7cb/8638968/eb258fc4ed75/pone.0260980.g001.jpg

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