PMID- 37421631
OWN - NLM
STAT- MEDLINE
DCOM- 20231102
LR  - 20231102
IS  - 1744-7607 (Electronic)
IS  - 1742-5255 (Linking)
VI  - 19
IP  - 6
DP  - 2023 Jan-Jun
TI  - A real-world data analysis of acetylsalicylic acid in FDA Adverse Event Reporting 
      System (FAERS) database.
PG  - 381-387
LID - 10.1080/17425255.2023.2235267 [doi]
AB  - BACKGROUND: Acetylsalicylic acid (Aspirin), one of the oldest medicines, is 
      widely used in various clinical fields. However, numerous adverse events (AEs) 
      have been reported. In this study, we aimed to investigate adverse drug reactions 
      (ADRs) of aspirin using real-worlddata from the US Food and Drug Administration 
      Adverse Event Reporting System (FAERS) database. METHODS: We assessed the 
      disproportionality of aspirin-related AEs by calculating measures such as 
      reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian 
      confidence propagationneural network (BCPNN), and Gamma-Poisson Shrinker (GPS). 
      RESULTS: Out of 7,510,564 casereports in the FAERS database, 18644 reports of 
      aspirin as the 'primary suspected (PS)' AEs were recorded. Disproportionality 
      analyses identified 493 aspirin-related preferred terms (PTs) across 25 organ 
      systems. Notably, unexpected significant AEs such as pallor (p=5.66E-33), 
      dependence (p=6.45E-67), and compartment syndrome (p=1.95E-28) were observed, 
      which were not mentioned in the drug's instructions. CONCLUSION: Our findings 
      align with clinical observations, highlighting potential new and unexpected ADR 
      signals associated with aspirin. Further prospective clinical studies are 
      necessary to confirm and elucidate the relationship between aspirin and these 
      ADRs. This study offers a fresh and unique perspective for studying drug-AEs.
FAU - Zhao, Bin
AU  - Zhao B
AUID- ORCID: 0000-0002-8165-3315
AD  - Xiamen Health and Medical Big Data Center (Xiamen Medicine Research Institute), 
      Xiamen, Fujian, China.
FAU - Zhang, Xiaohong
AU  - Zhang X
AD  - Department of Pathology, The 909th Hospital, School of Medicine, Xiamen 
      University, Zhangzhou, Fujian, China.
FAU - Chen, Moliang
AU  - Chen M
AD  - Xiamen Health and Medical Big Data Center (Xiamen Medicine Research Institute), 
      Xiamen, Fujian, China.
FAU - Wang, Yan
AU  - Wang Y
AD  - Medical Reproductive Center, People's Hospital of Jiuquan City, Jiuquan, Gansu, 
      China.
LA  - eng
PT  - Journal Article
DEP - 20230712
PL  - England
TA  - Expert Opin Drug Metab Toxicol
JT  - Expert opinion on drug metabolism & toxicology
JID - 101228422
RN  - R16CO5Y76E (Aspirin)
SB  - IM
MH  - United States
MH  - Humans
MH  - *Aspirin/adverse effects
MH  - Bayes Theorem
MH  - Adverse Drug Reaction Reporting Systems
MH  - *Drug-Related Side Effects and Adverse Reactions/epidemiology
MH  - United States Food and Drug Administration
MH  - Data Analysis
OTO - NOTNLM
OT  - Acetylsalicylic acid
OT  - Adverse drug reaction
OT  - Adverse event
OT  - Aspirin
OT  - Real-world data analysis
EDAT- 2023/07/08 21:05
MHDA- 2023/07/08 21:06
CRDT- 2023/07/08 13:03
PHST- 2023/07/08 21:06 [medline]
PHST- 2023/07/08 21:05 [pubmed]
PHST- 2023/07/08 13:03 [entrez]
AID - 10.1080/17425255.2023.2235267 [doi]
PST - ppublish
SO  - Expert Opin Drug Metab Toxicol. 2023 Jan-Jun;19(6):381-387. doi: 
      10.1080/17425255.2023.2235267. Epub 2023 Jul 12.