Switching to faricimab from the current anti-VEGF therapy: evidence-based expert recommendations
Bibliographic record
Abstract
Dual inhibition of the angiopoietin (Ang)/Tie and vascular endothelial growth factor (VEGF) signalling pathways in patients with retinal diseases, such as neovascular age-related macular degeneration (nAMD) and diabetic macular oedema (DME), may induce greater vascular stability and contribute to increased treatment efficacy and durability compared with treatments that only target the VEGF pathway. Faricimab, a bispecific intravitreal agent that inhibits both VEGF and Ang-2, is the first injectable ophthalmic drug to achieve treatment intervals of up to 16 weeks in Phase 3 studies for nAMD and DME while exhibiting improvements in visual acuity and retinal thickness. Data from real-world studies have supported the safety, visual and anatomic benefits and durability of faricimab, even in patients who were previously treated with other intravitreal agents. These evidence-based expert recommendations from a panel of retina specialists consolidate current evidence with clinical experience for the optimal use of faricimab in patients with nAMD or DME, with a focus on switching from an anti-VEGF agent to faricimab.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".