PMID- 38407147
OWN - NLM
STAT- Publisher
LR  - 20240226
IS  - 1542-6270 (Electronic)
IS  - 1060-0280 (Linking)
DP  - 2024 Feb 26
TI  - Safety Profile of Selective Serotonin Reuptake Inhibitors in Real-World Settings: 
      A Pharmacovigilance Study Based on FDA Adverse Event Reporting System.
PG  - 10600280241231116
LID - 10.1177/10600280241231116 [doi]
AB  - 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.
FAU - Zhao, Yi
AU  - Zhao Y
AUID- ORCID: 0000-0003-2555-2154
AD  - Department of Pharmacy, The Second Affiliated Hospital of Xi'an Jiaotong 
      University, Xi'an, China.
FAU - Zhang, Yuzhou
AU  - Zhang Y
AD  - School of Information Engineering, Engineering University of People's Armed 
      Police, Xi'an, China.
FAU - Yang, Lin
AU  - Yang L
AD  - Department of Pharmacy, Xi'an Central Hospital, Xi'an, China.
FAU - Zhang, Kanghuai
AU  - Zhang K
AD  - Department of Pharmacy, The Second Affiliated Hospital of Xi'an Jiaotong 
      University, Xi'an, China.
FAU - Li, Sha
AU  - Li S
AD  - Department of Pharmacy, The Second Affiliated Hospital of Xi'an Jiaotong 
      University, Xi'an, China.
LA  - eng
PT  - Journal Article
DEP - 20240226
PL  - United States
TA  - Ann Pharmacother
JT  - The Annals of pharmacotherapy
JID - 9203131
SB  - IM
OTO - NOTNLM
OT  - FAERS database
OT  - adverse events
OT  - antidepressant
OT  - data mining
OT  - depression
OT  - pharmacovigilance
COIS- Declaration of Conflicting InterestsThe authors declared no potential conflicts 
      of interest with respect to the research, authorship, and/or publication of this 
      article.
EDAT- 2024/02/26 12:44
MHDA- 2024/02/26 12:44
CRDT- 2024/02/26 11:01
PHST- 2024/02/26 12:44 [medline]
PHST- 2024/02/26 12:44 [pubmed]
PHST- 2024/02/26 11:01 [entrez]
AID - 10.1177/10600280241231116 [doi]
PST - aheadofprint
SO  - Ann Pharmacother. 2024 Feb 26:10600280241231116. doi: 10.1177/10600280241231116.