Efficacy and safety of prostaglandin analogues in patients with predominantly primary open-angle glaucoma or ocular hypertension: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: First-line therapy for primary open-angle glaucoma and ocular hypertension generally involves prostaglandin analogue therapy. The relative efficacy of differing prostaglandin therapy is disputed. METHODS: A meta-analysis was conducted of head-to-head randomized trials of prostaglandin therapies. We included randomized trials assessing head-to-head evaluations of prostaglandin analogues travoprost, latanoprost and bimatoprost in patients with predominantly primary open-angle glaucoma or ocular hypertension. Findings were interpreted in light of equivalence margins. RESULTS: Our search identified 16 eligible trials, of which 15 were included in the meta-analysis. Trials were, in general, poorly reported. We pooled 9 trials assessing IOP-lowering effects of travoprost vs latanoprost (total n = 1098, weighted mean difference [WMD], -0.24 mmHg, 95% CI, -0.87 to 0.38, P = 0.45, I2 = 56%, 95% CI, 0 to 0.77, heterogeneity P = 0.01). Eight trials assessed travoprost vs bimatoprost (total n = 714, WMD, 0.88 mmHg, 95% CI, 0.13 to 1.63, P = 0.02, I2 = 56%, 95% CI, 0% to 78%, heterogeneity P = 0.02). And 8 trials assessed latanoprost vs bimatoprost (total n = 943, WMD, 0.73 mmHg, 95% CI, 0.10 to 1.37, P = 0.02, I2 = 47%, 95% CI, 0% to 74%, heterogeneity P = 0.06). Travoprost was associated with greater incidence of conjunctival hyperemia than latanoprost (RR 5.71, 95% CI, 1.81 to 18.02, P </= 0.001, I2 = 97%, 95% CI, 95 to 98, P </= 0.001). Five trials assessing latanoprost and bimatoprost revealed an elevated risk of conjunctival hyperemia with bimatoprost (RR 1.59, 95% CI, 1.02 to 2.48, P = 0.04, I2 = 76%, 95% CI, 16 to 88, P = 0.002). CONCLUSION: Randomized head-to-head evaluations of prostaglandin therapy demonstrate similar efficacy effects, but differing hyperemia effects.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".