Early detection of neovascular age-related macular degeneration: an economic evaluation based on data from the EDNA study
Bibliographic record
Abstract
BACKGROUND/AIMS: To evaluate the cost-effectiveness of non-invasive monitoring tests to detect the onset of neovascular age-related macular degeneration (nAMD) in the unaffected second eye of patients receiving treatment for unilateral nAMD in a UK National Health Service (NHS) hospital outpatient setting. METHODS: A patient-level state transition model was constructed to simulate the onset, detection, and treatment of nAMD in the second eye. Five index tests were compared: self-reported change in visual function, Amsler test, clinic measured change in visual acuity from baseline, fundus assessment by clinical examination or colour photography, and spectral domain optical coherence tomography (SD-OCT). Diagnosis of nAMD was confirmed by fundus fluorescein angiography (FFA) before prompt initiation of antivascular endothelial growth factor treatment. Quality-adjusted life-years (QALYs) and costs of health and social care were modelled over a 25-year time horizon. RESULTS: SD-OCT generated more QALYs (SD-OCT, 5.830; fundus assessment, 5.787; Amsler grid, 5.736, patient's subjective assessment, 5.630; and visual acuity, 5.600) and lower health and social care costs (SD-OCT, £19 406; fundus assessment, £19 649; Amsler grid, £19 751; patient's subjective assessment, £20 198 and visual acuity, £20 444) per patient compared with other individual monitoring tests. Probabilistic sensitivity analysis indicated a high probability (97%-99%) of SD-OCT being the preferred test across a range of cost-effectiveness thresholds (£13 000-£30 000) applied in the UK NHS. CONCLUSIONS: Early treatment of the second eye following FFA confirmation of SD-OCT positive findings is expected to maintain better visual acuity and health-related quality of life and may reduce costs of health and social care over the lifetime of patients.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".