Underuse of Wide Excision for Primary Cutaneous Melanoma in the United States
Bibliographic record
Abstract
Three randomized trials support wide excision (WEX) for primary cutaneous melanoma. The objective was to evaluate WEX use for melanoma in the United States. Patients with localized melanoma were identified from the Surveillance, Epidemiology and End Results database between 1988 and 1997. Associations between predictor variables and WEX compared to biopsy alone were evaluated using logistic regression. Of 8,268 patients identified, 74.9 per cent had WEX, whereas 25.1 per cent had biopsy alone. WEX use peaked in 1990 at 81.6 per cent and was lowest in 1995 at 69.8 per cent. Overall, WEX use decreased over time. WEX use was independently associated with Breslow thickness (odds ratio [OR] per 1-mm depth of invasion 1.4, 95 per cent confidence interval [CI] 1.3, 1.5), and was inversely related to patient age (OR per 10 years of age 0.93; 95% CI 0.90, 0.96). As compared with the time period 1988 to 1990, WEX use declined during 1991 to 1993 (OR 0.71, 95% CI 0.60-0.83) and from 1994 to 1997 (OR 0.65; 95% CI 0.57-0.75). Many patients with localized melanoma undergo biopsy alone without a WEX. Use of WEX is associated with thicker melanomas and younger patients. Use of WEX has decreased over time, despite results from three randomized trials supporting its use.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".