One‐Year Effectiveness Study of Intravitreous Ranibizumab in Wet (Neovascular) Age‐Related Macular Degeneration: A Meta‐Analysis
Bibliographic record
Abstract
PURPOSE: The clinical efficacy of ranibizumab has been examined by a large number of prospective and retrospective studies to date. This meta-analysis was conducted to summarize the current body of evidence on visual acuity (VA) changes with use of ranibizumab in the treatment of wet (neovascular) age-related macular degeneration (wAMD). METHODS: A literature review of multiple electronic databases (EMBASE, MEDLINE, MedMEME) was conducted to find randomized controlled trials (RCTs) and observational studies that reported changes in VA while patients with wAMD were on ranibizumab. Study factors analyzed were baseline patient characteristics, study type, sample size, and 12-month change in VA. Data were pooled in a meta-analysis with VA change as the main outcome. Data were then stratified by study design and a meta-regression was conducted to assess 12-month VA change against baseline VA and age. RESULTS: A total of 42 studies were included for analysis. An overall increase of 5.58 letters (95% confidence interval [CI]: 4.42-6.75; p heterogeneity, < 0.001) was shown with use of ranibizumab compared to baseline. Improvements in VA were larger for RCTs, at 7.71 letters (95% CI: 6.66-8.76; p heterogeneity, 0.013), compared to observational studies, at 4.85 letters (95% CI: 3.32-6.38; p heterogeneity, < 0.001). The meta-regression showed a significant decrease in effect size between baseline VA and 12-month VA change. CONCLUSION: This meta-analysis suggests visual improvements at 12 months of 0.5-mg ranibizumab use in patients with wAMD. A higher gain in VA was observed when pooling results from RCTs compared to those in observational studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.077 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".