Effectiveness and safety of ranibizumab in patients with central retinal vein occlusion: results from the real-world, global, LUMINOUS study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness, treatment patterns and long-term safety of ranibizumab 0.5 mg in treatment-naïve patients with central retinal vein occlusion (CRVO) in a real-world setting. METHODS: LUMINOUS, a 5-year, global, prospective, multicentre, multi-indication, observational, open-label study, recruited treatment naïve or prior treated patients who were treated as per the local ranibizumab label. Here, we report the mean change in visual acuity (VA; Early Treatment Diabetic Retinopathy Study [ETDRS] letters), treatment exposure over year (Y) 1 and 5-year safety in treatment-naïve CRVO patients. RESULTS: At baseline, the mean age of treatment-naïve CRVO patients (n = 327) was 68.9 years, with a mean (Standard deviation [SD]) VA of 40.6 (23.9) letters. At Y1, patients (n = 144) had a mean (SD) VA gain from baseline of 10.8 (19.66) letters, with a mean (SD) of 5.4 (2.65) ranibizumab injections. Patients demonstrated mean (SD) VA gains of 2.7 (19.35), 11.6 (20.56), 13.9 (18.08), 11.1 (18.46) and 8.2 (24.86) letters with 1, 2-3, 4-5, 6-8 and >8 ranibizumab injections, respectively. Mean (SD) VA gains at Y1 in patients receiving loading (67.4%) and no loading dose (32.6%) was 11.9 (20.42) and 8.4 (17.99) letters, respectively. Over five years, the incidence of ocular/non-ocular adverse events (AEs) and serious AEs was 11.3%/8.6% and 1.2%/6.7%, respectively. CONCLUSIONS: These results demonstrate the effectiveness of ranibizumab in treatment-naïve CRVO patients at Y1 with clinically meaningful VA gains and no new safety findings over five years. These findings may help inform routine practice and enable better clinical management to achieve optimal visual outcomes.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".