Histological characteristics of metastasizing thin melanomas: a case-control study of 43 cases.
Bibliographic record
Abstract
OBJECTIVE: To study clinical and histological features associated with metastasizing thin melanomas (MTMs). DESIGN: Case-control study of clinicopathological features of patients with MTMs by a panel of 10 dermatopathologists. SETTING: Members of the North American Melanoma Pathology Study Group selected the cases from the melanoma databases at 8 academic institutions. PATIENTS: Forty-three patients with MTMs (<1 mm thick) and 42 control subjects without metastasis matched for age, sex, tumor site, and Breslow thickness. INTERVENTION: None. MAIN OUTCOME MEASURES: Clinical (age, sex, site of lesion, stage at diagnosis, metastasis site, disease-free survival, and outcome) and histological (Breslow thickness, Clark level, growth phase, regression, and inflammatory response) features of patients with MTMs vs controls. RESULTS: There was an overrepresentation of axial tumors among patients with MTMs. Extensive regression was present in 18 patients (42%) with MTM vs 2 matched control subjects (5%) (95% confidence interval, 21%-53%; P =.001). Other histological variables were not significantly different. Two patients had melanomas in situ with subsequent metastasis. CONCLUSIONS: Thin melanomas with extensive regression represent a group at higher risk for the development of metastasis. Furthermore, the risk of metastasis cannot be dismissed in cases of melanoma in situ.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".