Safety Profile of Selective Serotonin Reuptake Inhibitors in Real-World Settings: A Pharmacovigilance Study Based on FDA Adverse Event Reporting System

Author:

Zhao Yi1ORCID,Zhang Yuzhou2,Yang Lin3,Zhang Kanghuai1,Li Sha1

Affiliation:

1. Department of Pharmacy, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China

2. School of Information Engineering, Engineering University of People’s Armed Police, Xi’an, China

3. Department of Pharmacy, Xi’an Central Hospital, Xi’an, China

Abstract

Background: Selective serotonin reuptake inhibitors (SSRIs) are the most frequently prescribed agents to treat depression. Considering the growth in antidepressant prescription rates, SSRI-induced adverse events (AEs) need to be comprehensively clarified. Objective: This study was to investigate safety profiles and potential AEs associated with SSRIs using the Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: A retrospective pharmacovigilance analysis was conducted using the FAERS database, with Open Vigil 2.1 used for data extraction. The study included cases from the marketing date of each SSRI (ie, citalopram, escitalopram, fluoxetine, paroxetine, fluvoxamine, and sertraline) to April 30, 2023. We employed the reporting odds ratio and Bayesian confidence propagation neural network as analytical tools to assess the association between SSRIs and AEs. The Medical Dictionary for Regulatory Activities was used to standardize the definition of AEs. AE classification was achieved using system organ classes (SOCs). Results: Overall, 427 655 AE reports were identified for the 6 SSRIs, primarily associated with 25 SOCs, including psychiatric, nervous system, congenital, familial, genetic, cardiac, and reproductive disorders. Notably, sertraline ( n = 967) and fluvoxamine ( n = 169) exhibited the highest and lowest signal frequencies, respectively. All SSRIs had relatively strong signals related to congenital, psychiatric, and nervous disorders. Conclusions and relevance: Most of our findings are consistent with those reported previously, but some AEs were not previously identified. However, AEs attributed to SSRIs remain ambiguous, warranting further validation. Applying data-mining methods to the FAERS database can provide additional insights that can assist in appropriately utilizing SSRIs.

Funder

Research Fund of The Second Affiliated Hospital of Xi’an Jiaotong University

Publisher

SAGE Publications

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