Evidence map›Paper›PMID 40995193›Full record

ArticleTherapeutic advances in drug safety2025

Real-world large sample evaluation of drug-related blepharoptosis: a pharmacovigilance analysis of the FDA Adverse Event Reporting System database.

Kunhong Xiao, Xiaodong Chen, Shinan Wu, Yiyan Zhang, Ruiye Chen, Haixing Wu, Ziyi Qi, Jiahao Liu, Yuru Wang, Yanliang Miao and 2 more

Abstract read
In one paragraph

Article in Therapeutic advances in drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Kunhong XiaoDepartment of Ophthalmology and Optometry, Fujian Medical University, Fuzhou, China.ORCID https://orcid.org/0009-0008-7805-7193
Xiaodong ChenDepartment of Ophthalmology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Shinan WuDepartment of Ophthalmology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.ORCID https://orcid.org/0000-0002-6992-9059
Yiyan ZhangDepartment of Ophthalmology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, China.
Ruiye ChenCentre for Eye Research Australia, The Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia.
Haixing WuDepartment of Anesthesiology, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.
Ziyi QiNational Clinical Research Center for Eye Diseases, Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jiahao LiuCentre for Eye Research Australia, The Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia.
Yuru WangDepartment of Ophthalmology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Yanliang MiaoDepartment of Ophthalmology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Yan HuangDepartment of Ophthalmology and Optometry, Fujian Medical University, Fuzhou 350122, China.
Li LiDepartment of Ophthalmology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou 350001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

blepharoptosisdrug-related adverse eventspharmacovigilancereal-world study

Identifiers

PMID40995193
PMCPMC12454954

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.