Cost‐effectiveness analysis of staging strategies in patients with regionally metastatic melanoma
Bibliographic record
Abstract
PURPOSE: Variability exists regarding optimal staging for node-positive melanoma. Options include combinations of physical examination (PE), radiography, computed tomography (CT), and positron emission tomography (PET). Cost-effectiveness of regimens has never been investigated. METHODS: A modeled cost-effectiveness analysis was performed to examine the cost per surgery performed and per accurate diagnosis achieved with three staging regimens (PE/chest radiography, CT, PET/CT) for node-positive melanoma. Incremental cost-effectiveness ratios were used to compare regimens. Deterministic and probabilistic sensitivity analyses were undertaken to address variation in parameters. Costs are direct from the perspective of the Canadian single-payer system and 2012 valuations. RESULTS: Staging with PE/radiography is the least cost-effective option, resulting in greater costs than CT alone, and fewer accurate diagnoses. Compared to CT alone, PET/CT incurs greater incremental cost ($902.81CAD), but results in 4% fewer lymphadenectomies and 4% more accurate diagnoses. PET/CT costs $22,570.25CAD for each additional accurate diagnosis achieved compared to CT alone. Sensitivity analyses demonstrate that the optimal staging strategy is influenced by diagnostic test characteristics and the willingness-to-pay threshold, but robust to other varied parameters. CONCLUSIONS: PE/radiography appears to be the least cost-effective staging regimen. The benefit of PET/CT over CT alone depends on a health system's priorities and willingness-to-pay.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".