Partial Regression of Primary Cutaneous Melanoma
Bibliographic record
Abstract
Whether partial regression of a primary melanoma has an adverse impact on prognosis is controversial. As an indirect mechanism of addressing this question we drew a correlation between the histopathological characteristics of 107 cutaneous melanomas and the presence of sub-clinical metastasis in corresponding sentinel lymph nodes. Partial regression of the primary tumor, defined as focal replacement of the lesion by a scar, unrelated to a previous biopsy, was observed in 20 (19%) cases in the group as a whole. Excluding cases in which an accurate Breslow thickness of the primary melanoma could not be established and/or the presence of a capsular nevus was detected in the sentinel node, a total of 97 remained. Seventeen cases (Breslow thickness 0.63-9.7; mean 2.4 mm) showed partial regression and 80 (Breslow thickness 0.25-7.00; mean 1.8 mm) were devoid of regression. Of the 17 cases with regression 5 (29%) had nodal metastasis (by histopathology and/or molecular analysis) and of the 80 cases without regression 23 (29%) had nodal metastasis (by one or both evaluations). Our data reveals no association between partial regression of the primary melanoma and sentinel node involvement by the disease. The Breslow thickness proved to be the only significant independent variable related to nodal metastasis. Of interest, ulceration of the primary lesion was significantly associated with nodal disease on univariate, but not on multivariate, analysis. While acknowledging that the cohort size may lack the statistical power to demonstrate subtle associations, our data supports the known relevance of tumor thickness and ulceration to regional lymph node metastasis and thereby, to outcome of melanoma in its early stages, but fails to support a similar role for partial regression.
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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 | 0.000 |
| 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) | 0.002 | 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".