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基于 2004 年至 2024 年美国食品药品监督管理局的数据,探究与不安腿综合征相关的前 50 种药物
Authors Wei S, Song X, Chen R, Chen S, Lu B
Received 24 December 2024
Accepted for publication 11 April 2025
Published 15 May 2025 Volume 2025:17 Pages 929—946
DOI http://doi.org/10.2147/NSS.S513538
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Ahmed BaHammam
Shiju Wei,1 Xuhua Song,2 Rui Chen,1 Siyu Chen,1 Baoping Lu3
1The Second Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China; 2The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China; 3Institute of Hepatology, Laboratory for the Prevention and Treatment of Digestive System Diseases with Traditional Chinese Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China
Correspondence: Baoping Lu, Institute of Hepatology, Laboratory for the Prevention and Treatment of Digestive System Diseases with Traditional Chinese Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, 450046, People’s Republic of China, Email lbp1921@sohu.com
Background: Drugs-associated restless legs syndrome(RLS) can significantly impact patients’ quality of life. This study aims to identify the 50 most common drugs-associated with RLS in the FDA Adverse Event Reporting System (FAERS) database and track its epidemiological characteristics.
Methods: We extracted reports of adverse drug events related to restless legs syndrome from the FAERS database, covering the period from Q1 2004 to Q3 2024. We compiled a list of the 50 most frequently reported drugs based on RLS reports. Four risk signal detection methods were employed to assess whether valid signals were triggered by these drugs: Reporting Odds Ratio, Proportional Reporting Ratio, Multi-item Gamma Poisson Shrinker, and Information Component from the Bayesian Confidence Propagation Neural Network. Logistic regression evaluated risk factors, and the Weibull Shape Parameter (WSP) test analyzed time-to-onset (TTO).
Results: A total of 16,410 reports were linked to RLS, with sodium oxybate being the most common (648 cases, 3.9%). Nervous system medications comprised 31.3% of cases. Of the 50 drugs, 27 showed valid risk signals; only 6 were consistent with FDA labels. Risk factors included age under 44, weight over 64 kg, female gender, and 24 specific drugs. TTO analysis revealed that most drugs exhibited early onset patterns.
Conclusion: Our study highlights drugs potentially linked to drug-associated RLS emphasizing the need to consider these risks in clinical practice.
Keywords: restless legs syndrome, risk signal, FAERS, real-world data analysis, pharmacovigilance, drug-associated