Association of Anti-VEGF Therapy with Reported Ocular Adverse Events
Bibliographic record
Abstract
Objective Anti-vascular endothelial growth factor (VEGF) therapies have transformed the management of neovascular age-related macular degeneration, diabetic macular edema, and macular edema secondary to retinal vein occlusion (RVO). This class-wide pharmacovigilance study evaluated the disproportionality of reported ocular adverse events (AEs) among anti-VEGF agents using real-world data. Design A population-based, observational pharmacovigilance study. Participants Reports from the FDA Adverse Event Reporting System (FAERS) database (January 2004–September 2024) for individuals treated with anti-VEGF agents. Methods Ocular AEs were identified from FAERS, and disproportionality was assessed by comparing each anti-VEGF agent to background reporting using reporting odds ratios (RORs, 95% CI); signals were considered significant if IC 025 >0. Ranibizumab, aflibercept, brolucizumab, and faricimab were evaluated to compare ocular AE profiles amongst agents. Main Outcome Measures Disproportionality of reported ocular AEs among anti-VEGF agents. Results Across included patients receiving anti-VEGF agents with ocular AEs, most were female and aged 65–85 years. When comparing intraocular inflammation (IOI) signals across anti-VEGF agents, the strongest association was observed with brolucizumab (ROR=633.32), followed by faricimab (ROR=156.44), aflibercept (ROR=51.29), and ranibizumab (ROR=16.90). Faricimab was notably associated with elevated disproportionality signals for reports of anterior segment inflammation, including anterior chamber flare (ROR=270.95), unspecified anterior chamber inflammation (ROR=226.28), iridocyclitis (ROR=214.60), and iritis (ROR=88.90). For posterior segment involvement, increased reporting of vitritis was observed with brolucizumab (ROR=1769.33), faricimab (ROR=466.99), aflibercept (ROR=165.31), and ranibizumab (ROR=56.67), Rare but clinically significant complications were reported across all agents, including for reports of endophthalmitis (aflibercept ROR=208.88, ranibizumab ROR=114.69, faricimab ROR=99.75, brolucizumab ROR=56.15), non-infectious endophthalmitis (aflibercept, ROR=846.11, 244.42 for brolucizumab, 65.45 for ranibizumab, and 59.08 for faricimab), and pseudoendophthalmitis, which showed the strongest signal with faricimab (ROR=262.31; all 95%CI=29.37-649.50, P<0.0001, IC 025 >0). Faricimab also demonstrated increased reporting of retinal vascular inflammation but showed comparatively lower signals for non-inflammatory occlusive events and other serious ocular complications relative to other anti-VEGF agents. Conclusions This global pharmacovigilance study revealed variability in ocular AE reporting across anti-VEGF agents. Brolucizumab showed the strongest signal for intraocular inflammation, while aflibercept showed the highest signal for endophthalmitis. Continued real-world monitoring is warranted to define evolving safety profiles across anti-VEGF agents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".