Predictors of visual outcomes in patients with neovascular age‐related macular degeneration treated with anti‐vascular endothelial growth factor therapy: <i>post hoc</i> analysis of the <scp>VIEW</scp> studies
Bibliographic record
Abstract
PURPOSE: Identify predictors for response to anti-vascular endothelial growth factor (VEGF) therapy in patients with neovascular (wet) age-related macular degeneration (nAMD). METHODS: Retrospective, post hoc analysis of VIEW 1/2. Patients were randomized 1:1:1:1 to 0.5 mg intravitreal aflibercept (IVT-AFL) injection every 4 weeks (0.5q4); 2 mg IVT-AFL every 4 weeks (2q4); 2 mg IVT-AFL every 8 weeks (2q8) after an initial three injections at weeks 0, 4 and 8 or 0.5 mg intravitreal ranibizumab every 4 weeks (0.5q4). RESULTS: 1815 patients [IVT-AFL 2q4 (n = 613); IVT-AFL 2q8 (n = 607); ranibizumab 0.5q4 (n = 595)] were included. Baseline demographics/characteristics were evenly balanced. Younger age (49-69 years), lower visual acuity (VA) [10.0-≤45.0 Early Treatment Diabetic Retinopathy Study (ETDRS) letters] and smaller choroidal neovascularization (CNV) size [0.0-≤3.1 disc areas (DA)] at baseline were associated with the most vision gain (≥15 letters) over 52 weeks (all nominal p < 0.0001).Younger age, higher baseline VA (>64.0-≤83.0 letters) and smaller CNV size were associated with a VA ≥20/40 at week 52. Predominantly classic CNV at baseline (nominal p = 0.0007), older age (≥90 years), lower baseline VA (10.0-≤ 45.0 ETDRS letters) and larger CNV size (>10.1-≤32.6 DA) were all associated with a VA ≤20/200 at week 52 (all nominal p < 0.0001). Along with treatment (nominal p < 0.0001), lower VA (p = 0.0166) and smaller central retinal thickness (both nominal p = 0.0190) were predictors for dry retina development. CONCLUSION: Younger age, lower VA and smaller CNV size at baseline were all associated with greater vision gains over 52 weeks while younger age, higher VA and smaller CNV size at treatment start were more likely to achieve best-corrected VA 20/40 or better after a year's treatment, suggesting the benefit of early anti-VEGF treatment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".