ArticleBMJ open ophthalmology2025
Real-world faricimab switch in France: artificial intelligence-based detection of changes in exudative signs in difficult-to-treat neovascular age-related macular degeneration.
Article in BMJ open ophthalmology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Two-Year Real-World Outcomes of Faricimab in Treatment-Resistant Neovascular Age-Related Macular Degeneration.Clinical ophthalmology (Auckland, N.Z.) · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeSome patients with neovascular age-related macular degeneration (nAMD) have persistent signs of exudation under treatment with intravitreal injections of anti-vascular endothelial growth factor (VEGF) agents. We examined the real-world anatomical responses among patients with suboptimal response and switched to faricimab using artificial intelligence (AI)-based retinal fluid quantification.
methodsA retrospective, multicentric, cohort study of patients in France with exudative signs and switched to faricimab without a new loading phase, maintaining the same prior injection interval. The RetInSight Fluid Monitor AI software quantified subretinal (SRF) and intraretinal (IRF) fluid on spectral domain optical coherence tomography. The primary outcome was change in SRF and IRF volumes in the central 1 and 6 mm retinal areas after one and two injections of faricimab.
results74 patients (74 eyes) were included (mean age: 81.5±8.4 years, 49% male). Significant reductions were observed in mean 1 mm IRF (-2.9±18.3 nl; p=0.002), mean 6 mm IRF (-17.7±71.1 nl; p<0.001) and mean 6 mm SRF (-24.8±156.3 nl; p<0.001) volumes after one injection. The proportion of dry eyes (<5 nl for SRF and IRF in the 1 and 6 mm areas) increased from 0% at baseline to 32.4% after one injection and 48.4% after two injections. Lower baseline SRF volumes were predictive of dry response after one injection (
conclusionNearly half of patients achieved a dry response after two injections. AI-assisted fluid quantification provided objective monitoring, identifying lower baseline SRF and IRF as predictive factors for good response. Limited patient inclusion means longer-term and larger prospective studies are now required using automated retinal fluid quantification to further refine the baseline characteristics of good switch responders to better adapt switch protocols.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.