Cost-effectiveness analysis of standalone trabecular micro-bypass stents in patients with mild-to-moderate open-angle glaucoma in Canada
Bibliographic record
Abstract
Objectives: To estimate the cost-utility of two trabecular micro-bypass stents (TBS) implantation vs standard of care (SOC) in patients with mild-to-moderate open-angle glaucoma (OAG) in the Canadian healthcare setting. Methods: The deterioration in visual field (VF) defect over a 15-year time horizon was tracked using a Markov model with Hodapp-Parrish-Anderson stages of glaucoma (mild, moderate, advanced, severe/blind) and death as health states. Meta-analyses of randomized clinical trials were conducted to estimate the pooled reduction in intraocular pressure (IOP) and medication use due to TBS and SOC. The rate of decline in VF loss was adjusted by the extent of IOP reduction to estimate transition probabilities. Healthcare resource utilization, unit costs (2017 CAD), and progression-related utility scores were obtained by literature review, and medication costs with wastage were obtained from IMS Brogan PharmaStat. The impact of parameter and methodological uncertainty on costs and quality-adjusted life years (QALYs) was examined using probabilistic and 1-way sensitivity analyses. Results: The meta-analysis showed an additional reduction of 1.13 medications/patient and an additional decrease in IOP of –1.10 mmHg at 36 months favoring TBS. TBS strongly dominated medication alone, due to higher improvement in quality-of-life (0.068 QALYs), fewer blind eyes (–0.0031), and a decrease in total healthcare costs of C$2,908.3 per patient over the time horizon (C$9,394.1 TBS vs C$12,302.4 medication alone). Sensitivity analyses showed that results were robust to the uncertainties in model inputs and assumptions. Time-to-dominance was 44 months (3.7 years). Conclusions: The TBS procedure was cost-effective over SOC in a 15-year time horizon, with quality-of-life gains.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.013 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".