Effect of Brolucizumab and Aflibercept on the Maximum Thickness of Pigment Epithelial Detachments and Sub-Retinal Pigment Epithelium Fluid in HAWK and HARRIER
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of brolucizumab and aflibercept treatment in reducing the maximum thickness of pigment epithelial detachments (PEDs) and sub-retinal pigment epithelium (sub-RPE) fluid in patients with neovascular age-related macular degeneration in the HAWK and HARRIER studies. DESIGN: HAWK and HARRIER were 96-week, prospective, randomized, double-masked, controlled, multicenter studies. PARTICIPANTS: A total of 1775 patients across 11 countries were included in the HAWK study, and 1048 patients across 29 countries were included in the HARRIER study. INTERVENTION: After 3 monthly loading doses, brolucizumab-treated eyes received injections every 12 weeks or every 8 weeks if disease activity (DA) was detected. Aflibercept-treated eyes received fixed 8-week dosing. MAIN OUTCOME MEASURES: Maximum thickness of PEDs and sub-RPE fluid across the macula were assessed at baseline through week 96 in the brolucizumab- and aflibercept-treated patients and in the patient subgroups with DA at week 16 (matched in terms of injection number and treatment interval). RESULTS: At week 96, there were greater mean percentage reductions from baseline in maximum thickness of both PEDs and sub-RPE fluid in brolucizumab-treated patients vs. aflibercept-treated patients (PED: 19.7% [n = 336] vs. 11.9% [n = 335] in HAWK; 29.5% [n = 364] vs. 18.3% [n = 361] in HARRIER. Sub-RPE fluid: 75.4% vs. 57.3% in HAWK; 86.0% vs. 76.3% in HARRIER). A similar trend in mean percentage reductions was observed in patients with DA at week 16. CONCLUSIONS: This analysis shows that brolucizumab achieved greater reductions in PEDs and sub-RPE fluid thickness than aflibercept in HAWK and HARRIER. TRIAL REGISTRATION: ClinicalTrials.gov Identifiers: NCT02307682 (HAWK) and NCT02434328 (HARRIER). FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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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 | 0.001 | 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 | 0.001 |
| 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".