Comparative assessment of subretinal hyper-reflective material in patients treated with brolucizumab versus aflibercept in HAWK and HARRIER
Bibliographic record
Abstract
PURPOSE: Post hoc analysis of the phase III HAWK and HARRIER studies to compare the reductions in subretinal hyper-reflective material (SHRM) thickness following brolucizumab 6 mg or aflibercept 2 mg treatment and to assess SHRM thickness and thickness variability as a potential biomarker of visual outcomes in patients with neovascular age-related macular degeneration (nAMD). METHODS: Optical coherence tomography images from the brolucizumab (n=700) and aflibercept (n=696) arms were analysed for the maximum SHRM thickness across the macula over 96 weeks. In a pooled treatment-agnostic analysis, the effect of week 12 SHRM thickness and SHRM thickness variability on best-corrected visual acuity (BCVA) through week 96 were also assessed. RESULTS: Brolucizumab was associated with numerically higher percentage reductions from baseline in SHRM thickness versus aflibercept in all patients (week 96: 54.4% vs 47.6%, respectively) and also in the matched subgroups with disease activity at week 16 (week 96: 51.6% vs 33.8%, respectively). In eyes with lower SHRM measurements at week 12, mean BCVA gains from baseline were higher at week 96 (<200 µm, +6.47 Early Treatment Diabetic Retinopathy Study letters; ≥200 µm, +3.10 letters). Eyes with the lowest SHRM thickness variability from week 12 to week 96 showed the greatest mean BCVA gains from baseline (week 96: <12 µm, +7.42 letters; >71 µm, -2.95 letters). CONCLUSIONS: In HAWK and HARRIER, greater reductions in maximum SHRM thickness from baseline were observed with brolucizumab compared with aflibercept. Furthermore, the data suggest that SHRM thickness postloading and SHRM thickness variability over time are biomarkers for visual outcomes in patients with nAMD.
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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 | 0.000 |
| 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".