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Record W4415899526 · doi:10.1016/j.oret.2025.10.019

Comparative Analysis of Ocular Adverse Events between Aflibercept 8 mg and Faricimab

2025· article· en· W4415899526 on OpenAlexafffund
Moiz Lakhani, Marko M. Popovic, Abdullah Al-Ani, Deeksha Kundapur, Tara Gholamian, Emaan Chaudry, Keean Nanji, Nikhil S. Patil, Alessandro Feo, SriniVas R. Sadda, David Sarraf, Michael S. Ip, Peter J. Kertes, Rajeev H. Muni, Feisal A. Adatia, Karim F. Damji, Varun Chaudhary, Bernard Hurley

Bibliographic record

VenueOphthalmology Retina · 2025
Typearticle
Languageen
FieldMedicine
TopicOcular Diseases and Behçet’s Syndrome
Canadian institutionsKensington HealthSunnybrook Health Science CentreMcMaster UniversityUniversity of AlbertaUniversity of CalgaryUniversity of Ottawa
FundersFoundation Fighting BlindnessPhysicians' Services Incorporated Foundation
KeywordsAfliberceptAdverse effectRanibizumabMEDLINESafety profile

Abstract

fetched live from OpenAlex

To compare the ocular safety of intravitreal aflibercept injections and faricimab using population-based, global postmarketing data in a large pharmacovigilance study. Population-based, retrospective pharmacovigilance study. Patients for whom ocular adverse event (AE) reports were submitted to the U.S. FDA Adverse Event Reporting System (FAERS) between January 2004-June 2025, and for whom intravitreal aflibercept injections (2 mg or 8 mg, where dose was recorded) or faricimab were listed as the primary suspect drug, were included. After deduplication, disproportionality was assessed using reporting odds ratios (RORs, 95%CI). Safety signals were considered statistically significant if they met Evans’ criteria (ROR>2, χ 2 >4, n≥3), Bonferroni-adjusted p<0.0003, and Bayesian threshold IC 025 >0. Disproportionality signals for ocular adverse events associated with intravitreal aflibercept 2 mg, aflibercept 8 mg, and faricimab, using aflibercept 2 mg as the reference comparator given its longer market availability and well-established safety profile. Among 13,809,873 FAERS reports, 30,761 involved intravitreal aflibercept 2 mg (n=21,058), aflibercept 8 mg (n=727), or faricimab (n=8,976). After deduplication, 8,352 reports remained for aflibercept 2 mg, 327 for aflibercept 8 mg, 4,168 for faricimab, and 13,797,026 for other drugs. Most patients were aged 65–85 years; women comprised 48.6% of the 8 mg group, 39.9% of faricimab, and 20.8% of the 2 mg group. Aflibercept 8 mg showed the highest disproportionality for intraocular inflammation and infection-related events, including anterior chamber flare (ROR=1410.5), vitritis (853.3), retinal vasculitis (352.2), and infectious (1208.3) and sterile endophthalmitis (352.0), as well as blindness (71.1) and reduced visual acuity (74.6). Faricimab had the highest RORs for injection-related inflammatory and hemorrhagic events—hypopyon (112.8), retinal pigment epithelial tear (193.9), choroidal hemorrhage (142.3), and pseudoendophthalmitis (309.9)—while aflibercept 2 mg was more often associated with structural complications, including increased intraocular pressure (187.8), posterior capsule rupture (80.1), vitreous hemorrhage (76.9), and retinal detachment (20.8). All signals met Bonferroni-adjusted significance (p<0.0001) and Bayesian criteria (IC 025 >0). Aflibercept 8 mg showed strong signals for intraocular inflammation, vasculitis, and endophthalmitis, aflibercept 2 mg was linked to structural complications, and faricimab had the highest disproportionality for select immuno-vascular events. These findings delineate agent- and dose-specific safety profiles within a unified comparative framework and reinforce the critical need for ongoing postmarketing surveillance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.023
GPT teacher head0.346
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations5
Published2025
Admission routes2
Has abstractyes

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