Real-world treatment patterns and visual outcomes of faricimab in patients with diabetic macular oedema in the UK at 12 months: the FARWIDE-DMO study
Bibliographic record
Abstract
BACKGROUND: The Faricimab Real-World Evidence (FARWIDE) studies are evaluating real-world outcomes of eyes with diabetic macular oedema (DMO)/neovascular age-related macular degeneration (nAMD) treated with faricimab in the UK. We present results from FARWIDE-DMO for eyes with 12 months of follow-up after faricimab initiation. METHODS: FARWIDE-DMO includes patients with diagnosis of DMO who received ≥1 intravitreal faricimab injection after May 2022 in the diagnosed eye(s) at 1 of 35 UK National Health Service sites. All eyes had ≥12 months of follow-up after faricimab initiation as of July 2024. Treatment-naïve (TN) eyes had no prior anti-VEGF therapy or steroid implant. Previously treated (PT) eyes switched to faricimab. Baseline characteristics, visual acuity (VA) outcomes and treatment patterns were evaluated. Intraocular inflammation (IOI) and presumed infectious endophthalmitis (PIE) incidences were pooled for all nAMD/DMO eyes with any follow-up duration. Analyses are descriptive. RESULTS: 2147 eyes (1564 patients) were included (TN, 32.1%; PT, 67.9%). For TN eyes, mean (standard deviation [SD]) VA at baseline and 12 months were 63.9 (15.2) and 68.4 (16.3) Early Treatment Diabetic Retinopathy Study letters, respectively. VA remained stable in PT eyes. TN eyes received a mean (SD) of 4.5 (1.0) faricimab injections in months 1-6 and 1.9 (1.2) injections in months 7-12. PT eyes received 4.5 (1.2) injections in months 1-6 and 2.4 (1.3) in months 7-12. IOI and PIE rates were consistent with faricimab phase 3 trials. CONCLUSIONS: These 1-year data support real-world effectiveness, durability and safety of faricimab in DMO.
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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".