108384
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.4 Breast Cancer (Dove Med Press)
- 3.2 Clin Epidemiol
- 2.6 Cancer Manag Res
- 2.9 Infect Drug Resist
- 3.7 Clin Interv Aging
- 5.1 Drug Des Dev Ther
- 3.1 Int J Chronic Obstr
- 6.6 Int J Nanomed
- 2.6 Int J Women's Health
- 2.9 Neuropsych Dis Treat
- 2.8 OncoTargets Ther
- 2.0 Patient Prefer Adher
- 2.2 Ther Clin Risk Manag
- 2.5 J Pain Res
- 3.0 Diabet Metab Synd Ob
- 3.2 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 1.8 Pharmgenomics Pers Med
- 2.0 Risk Manag Healthc Policy
- 4.1 J Inflamm Res
- 2.0 Int J Gen Med
- 3.4 J Hepatocell Carcinoma
- 3.0 J Asthma Allergy
- 2.2 Clin Cosmet Investig Dermatol
- 2.4 J Multidiscip Healthc
已发表论文
依夫加替莫德α上市后的安全性问题：基于美国食品药品监督管理局不良事件报告系统数据库的药物警戒分析
Authors Huang J , Ye H, Lin J, Luo D, Huang P, Zheng X
Received 28 December 2024
Accepted for publication 10 September 2025
Published 16 September 2025 Volume 2025:17 Pages 765—778
DOI https://doi.org/10.2147/CLEP.S514738
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 5
Editor who approved publication: Professor Henrik Sørensen
Jinlong Huang,1,2 Hanyun Ye,1 Jingyang Lin,3 Dan Luo,1,2 Ping Huang,1 Xiaochun Zheng1,2
1Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China; 2School of Pharmacy, Hangzhou Normal University, Hangzhou, Zhejiang, People’s Republic of China; 3Heart Center, Department of Cardiovascular Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China
Correspondence: Ping Huang, Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, 158 Shangtang Road, Gongsu District, Hangzhou, Zhejiang, 310014, People’s Republic of China, Email huangpwly@sina.com Xiaochun Zheng, Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, 158 Shangtang Road, Gongsu District, Hangzhou, Zhejiang, 310014, People’s Republic of China, Email 13868109173@126.com
Aim: Efgartigimod alfa (EA) is a novel US Food and Drug Administration (FDA) approved neonatal Fc receptor-targeting drug; however, its real-world adverse event (AE) profile remains underexplored.
Methods: AE reports primarily related to EA were retrieved from the US FDA Adverse Event Reporting System database for the fourth quarter of 2021 to the third quarter of 2024. Disproportionality analysis using Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms was employed to detect signals of AEs.
Results: Our study processed 3,182 AE reports related to EA, revealing 57 signals that met the criteria of the ROR, PRR, Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms across 14 system organ classes. Notably, the most significant signal in the System Organ Class was “Surgical and medical procedures”, whereas the most significant signal in Preferred Term was “Bulbar Palsy”. Some unexpected over-the-counter AEs, including falls, choking, sepsis, nephrolithiasis, and atrial fibrillation, were also observed. The median onset time of EA-related AEs was 101.5 d (interquartile range 27– 260). The AE risk model associated with EA should be referred to as “early failure”, with the likelihood of AEs decreasing over time.
Conclusion: This study highlights the potential AEs and risks associated with the clinical use of EA; the analysis provides significant evidence regarding the clinical safety of EA.
Keywords: efgartigimod alfa, myasthenia gravis, signal mining, adverse events
1Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China; 2School of Pharmacy, Hangzhou Normal University, Hangzhou, Zhejiang, People’s Republic of China; 3Heart Center, Department of Cardiovascular Medicine, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, People’s Republic of China
Correspondence: Ping Huang, Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, 158 Shangtang Road, Gongsu District, Hangzhou, Zhejiang, 310014, People’s Republic of China, Email huangpwly@sina.com Xiaochun Zheng, Center for Clinical Pharmacy, Cancer Center, Department of Pharmacy, Zhejiang Provincial People’s Hospital (Affiliated People’s Hospital), Hangzhou Medical College, 158 Shangtang Road, Gongsu District, Hangzhou, Zhejiang, 310014, People’s Republic of China, Email 13868109173@126.com
Aim: Efgartigimod alfa (EA) is a novel US Food and Drug Administration (FDA) approved neonatal Fc receptor-targeting drug; however, its real-world adverse event (AE) profile remains underexplored.
Methods: AE reports primarily related to EA were retrieved from the US FDA Adverse Event Reporting System database for the fourth quarter of 2021 to the third quarter of 2024. Disproportionality analysis using Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms was employed to detect signals of AEs.
Results: Our study processed 3,182 AE reports related to EA, revealing 57 signals that met the criteria of the ROR, PRR, Bayesian Confidence Propagation Neural Network, and Multi-item Gamma Poisson Shrinker algorithms across 14 system organ classes. Notably, the most significant signal in the System Organ Class was “Surgical and medical procedures”, whereas the most significant signal in Preferred Term was “Bulbar Palsy”. Some unexpected over-the-counter AEs, including falls, choking, sepsis, nephrolithiasis, and atrial fibrillation, were also observed. The median onset time of EA-related AEs was 101.5 d (interquartile range 27– 260). The AE risk model associated with EA should be referred to as “early failure”, with the likelihood of AEs decreasing over time.
Conclusion: This study highlights the potential AEs and risks associated with the clinical use of EA; the analysis provides significant evidence regarding the clinical safety of EA.
Keywords: efgartigimod alfa, myasthenia gravis, signal mining, adverse events