A comparison of clinical trial and model-based cost estimates in glaucoma – The case of repeat laser trabeculoplasty In Ontario
Bibliographic record
Abstract
Economic evaluations of glaucoma interventions require accurate costs in addition to effectiveness data. However, the impact of different costing methods on cost estimates has not been investigated. Direct cost estimates alongside clinical trials may be labour-intensive and expensive, modelled cost using literature sources and institutional experience may be an alternative. We investigated modeled and directly collected costs of a trial comparing argon- and selective-laser trabeculoplasty (ALT and SLT) among glaucoma patients at St. Joseph’s Health Care in London, ON between 2013 and 2014, also comparing ministry and societal perspectives and cost drivers. Model and trial cost estimates differed minimally for the ministry perspective (8% and 4% for ALT and SLT) despite differences in modeled and observed parameter values and treatment pathways. Labour accounted for 90% of total cost. Costs were similar for the societal perspective although there was sensitivity to assumptions regarding patient time loss. Indirect costs were at least as large as direct medical costs. Modeled costs were an acceptable substitute for directly measured costs in this scenario.
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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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".