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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".