Related Experiment Video
Updated: Jul 20, 2026
In Vivo Vascular Injury Readouts in Mouse Retina to Promote Reproducibility
Published on: April 21, 2022
Signals of Drug-Related Retinal Fibrosis: Findings From a 20-Year Disproportionality Analysis of Global Spontaneous
Mingyan Wei1, Xiaodong Chen2, Ke Feng2
1Department of Ophthalmology, The First Affiliated Hospital of University of South China, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Purpose:
This study aimed to identify potential drugs associated with drug-related retinal fibrosis (RF) and to analyze their risk characteristics systematically.
Methods:
This study used a retrospective disproportionality analysis to identify significant drug signals associated with RF from over 17 million reports in the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. The identified drugs were categorized by therapeutic class, risk level, latency period, and key subgroups (e.g., age, gender, off-label use).
Results:
Sixteen drugs showed a significant association with RF, including anti-neovascularization agents, corticosteroids, and immunosuppressants. Risk severity varied: Verteporfin, ranibizumab, and brolucizumab had the highest risk, and vigabatrin and sildenafil had a relatively lower risk. The latency periods differed significantly, ranging from a median of 950 days for fluocinolone acetonide to 13 days for triamcinolone. Subgroup analysis revealed that off-label use increased the risk of RF and uncovered distinct susceptibility patterns: Adolescents (0-17 years) faced a higher risk when using specific drug classes such as corticosteroids, whereas elderly patients (≥65 years) were more susceptible to RF when using anti-neovascularization agents. Females showed a higher risk associated with immunosuppressants.
Conclusions:
This study presents a list of drugs associated with RF, providing a valuable reference to guide rational drug use, preserve visual acuity, and prevent irreversible structural damage.
Translational Relevance:
Identifying specific drugs associated with RF is crucial for preventing drug-related RF and developing personalized monitoring strategies.
