Therapeutic advances in drug safety · 2025
Real-world large sample evaluation of drug-related blepharoptosis: a pharmacovigilance analysis of the FDA Adverse Event Reporting System database.
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Xiao Kunhong, Chen Xiaodong, Wu Shinan, Zhang Yiyan, Chen Ruiye, Wu Haixing, Qi Ziyi, Liu Jiahao, Wang Yuru, Miao Yanliang, Huang Yan, Li Li
Аннотация
BACKGROUND: Blepharoptosis is one of the most common eyelid disorders in clinical ophthalmology. Previous evidence on drug-related blepharoptosis limited to case reports.
OBJECTIVES: This study aims to systematically evaluate the disproportionality signals of drugs associated with blepharoptosis using large-scale real-world data from the US FDA Adverse Event Reporting System (FAERS).
DESIGN: A retrospective disproportionality analysis was conducted based on the FAERS database.
METHODS: A total of 21,838,627 reports from the FAERS database, spanning 2004 to 2024, were included, with 19,541,994 reports retained after deduplication. Disproportionality analysis methods including reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker were employed to detect positive signals. The therapeutic purposes of the drugs, drug-related reporting patterns, drug signals strength, and onset times of adverse reactions were comprehensively assessed.
RESULTS: A total of 9324 cases of blepharoptosis were confirmed, involving 20 identified with significant signals. They primarily include antineoplastic and immunomodulating agents, sensory organ drugs, and neuropsychiatric drugs. Eleven drugs had previously been reported to be associated with blepharoptosis, while 9 were newly identified. Botulinum toxin A, ravulizumab, and latanoprost were found to exhibit the strongest signals. Neuropsychiatric drugs (e.g., lidocaine) had a median onset time of 1-9 days, while antineoplastic and immunomodulating agents (e.g., ravulizumab) had a median onset time of 164-912 days. Avelumab and rosuvastatin showed stronger signals for elderly males, while botulinum toxin A and bupivacaine were more significant for younger females.
CONCLUSION: This study validates known associations such as immune checkpoint inhibitors and neuroregulatory agents, and identifies drug-related signals. There are significant differences in the onset times of adverse reactions across drug categories, suggesting the need for targeted monitoring.
OBJECTIVES: This study aims to systematically evaluate the disproportionality signals of drugs associated with blepharoptosis using large-scale real-world data from the US FDA Adverse Event Reporting System (FAERS).
DESIGN: A retrospective disproportionality analysis was conducted based on the FAERS database.
METHODS: A total of 21,838,627 reports from the FAERS database, spanning 2004 to 2024, were included, with 19,541,994 reports retained after deduplication. Disproportionality analysis methods including reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker were employed to detect positive signals. The therapeutic purposes of the drugs, drug-related reporting patterns, drug signals strength, and onset times of adverse reactions were comprehensively assessed.
RESULTS: A total of 9324 cases of blepharoptosis were confirmed, involving 20 identified with significant signals. They primarily include antineoplastic and immunomodulating agents, sensory organ drugs, and neuropsychiatric drugs. Eleven drugs had previously been reported to be associated with blepharoptosis, while 9 were newly identified. Botulinum toxin A, ravulizumab, and latanoprost were found to exhibit the strongest signals. Neuropsychiatric drugs (e.g., lidocaine) had a median onset time of 1-9 days, while antineoplastic and immunomodulating agents (e.g., ravulizumab) had a median onset time of 164-912 days. Avelumab and rosuvastatin showed stronger signals for elderly males, while botulinum toxin A and bupivacaine were more significant for younger females.
CONCLUSION: This study validates known associations such as immune checkpoint inhibitors and neuroregulatory agents, and identifies drug-related signals. There are significant differences in the onset times of adverse reactions across drug categories, suggesting the need for targeted monitoring.