Adverse Event Signal Mining and Drug Risk Analysis of Sunitinib Based on FAERS Database
10.3870/j.issn.1004-0781.2025.01.017
- VernacularTitle:基于FAERS数据库对舒尼替尼不良事件信号挖掘和用药风险分析
- Author:
Susu LI
1
;
Zengqing MA
1
;
Lianping WU
1
;
Xin ZHAO
1
Author Information
1. 江苏大学附属高淳医院药学部,南京 211300
- Publication Type:Journal Article
- Keywords:
Sunitinib;
Adverse events;
Food and Drug Administration Adverse Event Reporting System(FAERS)database;
Signal mining
- From:
Herald of Medicine
2025;44(1):125-131
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore adverse event(AE)signals of sunitinib and to provide a reference for rational drug monitoring based on the Food and Drug Administration Adverse Event Reporting System(FAERS)database.Methods Report odds ratio method(ROR),proportional report ratio method(PRR),polynomial gamma Poisson distribution reduction method(MGPS),and Bayesian confidence interval progressive neural network method(BCPNN)were used to detect the data risk signal strength of sunitinib from the first quarter of 2006 to the third quarter of 2023.Results A total of 35 720 AE reports of sunitinib were retrieved,with 310 positive signals.Most AEs occurred in the first 30 days after treatment(39.71％).Serious AE accounted for 76.37％;27 system organ classifications(SOCs)were involved in positive signals,and the top three were systemic diseases,various reactions at the administration site,gastrointestinal system diseases,and various examinations.High frequency of death,diarrhea,disease progression,and fatigue;65％of the top 20 AEs were new adverse reactions,such as tumor rupture and diffuse proliferation of uveal melanocytes.Conclusion The evaluation of sunitinib should be improved,and medication monitoring should be strengthened to ensure the safety of patients.
