Three-Year Outcomes of Aflibercept Treatment for Neovascular Age-Related Macular Degeneration: Evidence from a Clinical Setting
Bibliographic record
Abstract
INTRODUCTION: To report 3-year treatment outcomes with intravitreal aflibercept injections for neovascular age-related macular degeneration (nAMD) in routine clinical practice. METHODS: This was a retrospective, single-centre, non-randomized interventional case series analysis. Data from treatment-naïve patients with nAMD treated between 1 October 2013 and 31 February 2014 were included in the analysis. Data including age, gender, vision acuity (VA) measured on Early Treatment of Diabetic Retinopathy Study charts (ETDRS) and injection numbers were recorded. Spectral domain optical coherence tomography (SD-OCT) data including presence or absence of macular fluid and automated central subfield macular thickness (CSMT) at year 1, 2 and 3 were also recorded. RESULTS: Of the 157 eyes of 148 patients treated, data from 108 eyes of 102 patients were available at 3-year follow-up. The mean (± SD) age was 80.6 ± 8.3 years with a mean of 154.5 ± 5.4 weeks follow-up. The mean VA changed from 54.4 ± 16 letters at baseline to 60.3 ± 18.1 letters (VA gain 5.9 ± 13.8 letter gain) at 1 year, to 60.8 ± 17.4 letters (VA gain 6.4 ± 14.9 letters) at 2 years and to 61.0 ± 16.6 letters (VA gain 6.6 ± 15.4 letters) at 3 years. The reduction in CSMT was 77.9 ± 101.4 µm with absence of macular fluid in 71% of eyes. The total mean number of injections was 15.9 ± 6.1 at year 3. CONCLUSION: The results suggest that good long-term morphological and functional treatment outcomes can be achieved using aflibercept for nAMD in a clinical setting.
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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".