Population-Based Estimates of Survival and Cost for Metastatic Melanoma
Bibliographic record
Abstract
BACKGROUND: Fewer than half of all patients with metastatic melanoma survive more than 1 year. Standard treatments have had little success, but recent therapeutic advances offer the potential for an improved prognosis. In the present study, we used population-based administrative data to establish real-world baseline estimates of survival outcomes and costs against which new treatments can be compared. METHODS: Data from administrative databases and patient registries were used to find a cohort of patients with metastatic melanoma in Ontario. To identify individuals most likely to receive new treatments, we focused on patients eligible for second-line treatment. The identified cohort had two characteristics: no surgical resection beyond primary skin excision, and receipt of first-line systemic therapy. RESULTS: Patient characteristics, Kaplan-Meier survival curves, and mean costs are reported. Of the 33,585 patients diagnosed with melanoma in Ontario from 1 January 1991 to 31 December 2010, 278 met the study inclusion criteria. Average age was 63 years, and 62% of the patients were men. Overall survival was estimated to be 19%, 12%, and 6% at 12, 24, and 60 months respectively. Mean survival time was 11.5 months, and mean cost was $30,685. CONCLUSIONS: Our baseline estimates indicate that survival outcomes are poor and costs are high for patients receiving standard treatment. Understanding the relative improvement accruing from any new treatment requires a comparison with the existing standard of care.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".