A United Kingdom-based economic evaluation of ranibizumab for patients with retinal vein occlusion (RVO)
Bibliographic record
Abstract
OBJECTIVE: This study compares the cost-effectiveness of intravitreal ranibizumab vs observation and/or laser photocoagulation for treatment of macular edema secondary to retinal vein occlusion in a UK-based model. METHODS: A Markov model was constructed using transition probabilities and frequency of adverse events derived using data from the BRAVO, CRUISE, and HORIZON trials. Outcomes associated with treatments and health states were combined to predict overall health costs and outcomes for cohorts treated with each option. RESULTS: In branch retinal vein occlusion, ranibizumab produced a gain of 0.518 quality-adjusted life years at an incremental cost of £8141, compared with laser photocoagulation. The incremental cost-effectiveness ratio was £15,710 per quality-adjusted life year, and the incremental cost per month free from blindness was £658. In central retinal vein occlusion, ranibizumab produced a gain of 0.539 quality-adjusted life years at an incremental cost of £9216, compared with observation only. The incremental cost-effectiveness ratio was £17,103, and the incremental cost per month free from blindness was £423. CONCLUSIONS: These incremental cost-effectiveness ratios are below the £20,000-30,000 range typically accepted as a threshold for cost-effectiveness. This suggests that ranibizumab may be regarded as a cost-effective therapy for patients with macular edema secondary to retinal vein occlusion, relative to grid laser photocoagulation (for BRVO) and observation (for CRVO). Limitations include sparse data for utilities associated with the severity of visual impairment in the WSE in patients with RVO. A lack of direct comparative evidence between ranibizumab and the dexamethasone intravitreal implant for the treatment of BRVO and CRVO and the infeasibility of an indirect comparison due to significant heterogeneity in trial designs prevented the inclusion of this treatment as a comparator in the Markov model.
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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 | 0.002 | 0.001 |
| 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".