Combination verteporfin photodynamic therapy ranibizumab-dexamethasone in choroidal neovascularization due to age-related macular degeneration: results of a phase II randomized trial
Bibliographic record
Abstract
Purpose: To assess whether combination therapy (CT) reduces retreatments when compared to ranibizumab monotherapy (RM), while safely maintaining similar vision outcomes. Methods: In this 24-month trial, patients with age-related macular degeneration (AMD) were randomized to 1) quarter-fluence or 2) half-fluence triple therapy (verteporfin photodynamic therapy [vPDT] + ranibizumab + dexamethasone), 3) half-fluence double therapy (vPDT + ranibizumab), or 4) RM. The primary outcomes were number of retreatment visits and change from baseline in visual acuity (VA) at 12 months. Results: One hundred sixty-two subjects enrolled. There were 4.0 ( P =0.02), 3.2 ( P <0.001), 4.1 ( P =0.03), and 5.7 retreatment visits through month 12, and 5.9 ( P =0.03), 4.3 ( P <0.001), 5.9 ( P =0.02) and 8.7 through month 24, in groups 1, 2, 3, and 4, respectively ( P -value comparing with RM). Month 12 VA score change from baseline (95% confidence interval) was +3.6 (–0.9 to +8.1), +6.8 (+2.4 to +11.1), +5.0 (+0.6 to +9.3), and +6.5 (+1.7 to +11.4), respectively. Conclusion: CT resulted in significantly fewer retreatment visits than a RM regimen at months 12 and 24. VA results appeared similar although wide confidence intervals preclude conclusions regarding vision outcomes. Keywords: age-related macular degeneration (AMD), combination therapy, ranibizumab, photodynamic therapy (PDT), verteporfin
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".