Ranibizumab in Diabetic Macular Oedema – A Benefit–risk Analysis of Ranibizumab 0.5 mg PRN Versus Laser Treatment
Bibliographic record
Abstract
INTRODUCTION: The structured Benefit-risk Action Team (BRAT) approach aims to assist healthcare decision makers in treatment assessments. We applied BRAT to compare the benefit-risk profile of ranibizumab 0.5 mg versus laser photocoagulation for the treatment of diabetic macular oedema (DMO). METHODS: One-year data for the ranibizumab 0.5 mg pro re nata (PRN) and laser arms of the phase III trials RESPOND (NCT01135914; n=220), RESTORE (NCT00687804; n=345), and REVEAL (NCT00989989; n=396) were included in the analysis. The benefit measures included ≥10 letters gain/avoidance of loss in best-corrected visual acuity (BCVA), achieving central retinal thickness (CRT) <275 μm, and 25-item Visual Function Questionnaire (VFQ-25) outcomes. The risks measures included endophthalmitis, intraocular pressure increase, hypertension, proteinuria, arterial/venous thromboembolic events and deaths. RESULTS: Ranibizumab treatment provided significant benefits compared with laser for ≥10 letter BCVA gain at month 12 (387/1,000 versus 152/1,000 patients), CRT <275 μm at 12 months (474/1,000 versus 348/1,000 patients), and improvement of ≥6.06 on the VFQ-25 near activities subscale (325/1,000 versus 245/1,000 patients). Results for the risk measures were similar for both treatments. CONCLUSIONS: Superior clinically relevant outcomes were observed with ranibizumab 0.5 mg PRN compared with laser without compromising on safety. This analysis further supports the positive benefit-risk profile of ranibizumab 0.5 mg PRN.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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".