Comparative Real-World Efficacy of Anti-Vascular Endothelial Growth Factor Agents in Neovascular Age-Related Macular Degeneration: A Multicenter Retrospective Study
Bibliographic record
Abstract
Introduction: This study directly compared the real-world effectiveness of bevacizumab, aflibercept 2 mg, and ranibizumab as first-line treatments for neovascular age-related macular degeneration (nvAMD). METHODS: A multicenter retrospective cohort of treatment-naïve nvAMD eyes managed with a treat-and-extend regimen in Israel and Canada. Primary outcomes were changes in visual acuity (VA) and central retinal thickness (CRT). Secondary outcomes included treatment burden (total injections and final maintained interval), non-response (persistent/worsening exudation or functional decline despite adequate treatment), non-extension (final interval of 4 weeks), and absence of active exudation. RESULTS: A total of 322 eyes received bevacizumab (n = 174), aflibercept (n = 110), or ranibizumab (n = 38) over a mean follow-up of 16.75 ± 12.66 months. Mean VA improved from 0.77 ± 0.47-0.60 ± 0.45 logarithm of the minimum angle of resolution following an average of 10.5 ± 6.3 injections. Aflibercept produced greater CRT reduction (-51.94 μm; p < 0.001), fewer injections (-2.35; p = 0.001), longer final intervals (+2.14 weeks; p < 0.001), and lower odds of non-response (adjusted odds ratio [aOR] 0.016; p < 0.001) and non-extension (aOR 0.128, p < 0.001) versus bevacizumab. It showed the largest mean VA gain, just short of significance on multivariable analysis (p = 0.059). Ranibizumab showed greater CRT reduction (-44.53 μm; p = 0.012) and lower non-extension odds (aOR 0.079; p = 0.001) than bevacizumab but did not significantly reduce treatment burden or improve VA. CONCLUSION: In this first real-world, head-to-head comparison, aflibercept and ranibizumab outperformed bevacizumab in key anatomic and treatment-efficiency outcomes, with aflibercept showing the most consistent advantages. These findings highlight clinically relevant differences among anti-vascular endothelial growth factor agents and underscore the importance of real-world data to guide nvAMD management. .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".