PMID- 34918584
OWN - NLM
STAT- MEDLINE
DCOM- 20220322
LR  - 20220429
IS  - 1744-764X (Electronic)
IS  - 1474-0338 (Linking)
VI  - 21
IP  - 4
DP  - 2022 Apr
TI  - A real-world pharmacovigilance study of axitinib: data mining of the public 
      version of FDA adverse event reporting system.
PG  - 563-572
LID - 10.1080/14740338.2022.2016696 [doi]
AB  - BACKGROUND: Axitinib was approved for treatment of advanced renal cell carcinoma 
      (RCC). The current study was to assess axitinib-related adverse events (AEs) 
      through data mining of the US Food and Drug Administration Adverse Event 
      Reporting System (FAERS). METHODS: Disproportionality analyses, including the 
      reporting odds ratio (ROR), the proportional reporting ratio (PRR), the Bayesian 
      confidence propagation neural network (BCPNN), and the multi-item gamma Poisson 
      shrinker (MGPS) algorithms, were employed to quantify the signals of 
      axitinib-associated AEs. RESULTS: Out of 10,703,806 reports collected from the 
      FAERS database, 9044 reports of axitinib as the 'primary suspected (PS)' AEs were 
      identified. Axitinib induced AEs occurrence targeted 26 organ systems. A total of 
      95 significant disproportionality PTs conforming to the four algorithms were 
      simultaneously retained. Rare reports and significant signals of aortic disease 
      have emerged. Unexpected significant AEs such as scrotal swelling, scrotal 
      ulcers, infections, and infestations might also occur. The median onset time of 
      axitinib-associated AEs was 63.5 days (interquartile range [IQR] 20-182 days), 
      and most of the cases occurred within the first one and 2 months after axitinib 
      initiation. CONCLUSION: Our study found potential new AEs signals and might 
      provide important support for clinical monitoring and risk identification of 
      axitinib.
FAU - Shu, Yamin
AU  - Shu Y
AD  - Department of Pharmacy, Tongji Hospital, Tongji Medical College of Huazhong 
      University of Science and Technology, Wuhan, China.
FAU - Ding, Yufeng
AU  - Ding Y
AD  - Department of Pharmacy, Tongji Hospital, Tongji Medical College of Huazhong 
      University of Science and Technology, Wuhan, China.
FAU - Dai, Bing
AU  - Dai B
AD  - West China Pharmaceutical College, Sichuan University, Chengdu, China.
FAU - Zhang, Qilin
AU  - Zhang Q
AD  - Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong 
      University of Science and Technology, Wuhan, China.
LA  - eng
PT  - Journal Article
DEP - 20211231
PL  - England
TA  - Expert Opin Drug Saf
JT  - Expert opinion on drug safety
JID - 101163027
RN  - C9LVQ0YUXG (Axitinib)
SB  - IM
MH  - Adverse Drug Reaction Reporting Systems
MH  - Axitinib/adverse effects
MH  - Bayes Theorem
MH  - Data Mining
MH  - Databases, Factual
MH  - *Drug-Related Side Effects and Adverse Reactions/epidemiology
MH  - Humans
MH  - *Pharmacovigilance
MH  - United States
MH  - United States Food and Drug Administration
OTO - NOTNLM
OT  - Axitinib
OT  - FAERS
OT  - adverse event
OT  - data mining
OT  - pharmacovigilance
OT  - renal carcinoma
EDAT- 2021/12/18 06:00
MHDA- 2022/03/23 06:00
CRDT- 2021/12/17 08:39
PHST- 2021/12/18 06:00 [pubmed]
PHST- 2022/03/23 06:00 [medline]
PHST- 2021/12/17 08:39 [entrez]
AID - 10.1080/14740338.2022.2016696 [doi]
PST - ppublish
SO  - Expert Opin Drug Saf. 2022 Apr;21(4):563-572. doi: 10.1080/14740338.2022.2016696. 
      Epub 2021 Dec 31.