Primary large cell neuroendocrine carcinoma of the skin: An under‐recognized entity and a mimic of metastatic disease
Bibliographic record
Abstract
Primary large cell neuroendocrine carcinomas of the skin are exceptionally rare and can be diagnosed only when a metastasis from another organ has been excluded. We report the case of a 62-year-old woman with a cutaneous papule on the mid-chest which generated a differential diagnosis of vascular lesion and basal cell carcinoma. Following excision, microscopic evaluation revealed a dermal large cell undifferentiated carcinoma, with a brisk mitotic rate and focal geographic necrosis. Mucin production was absent. On immunohistochemistry, the lesion expressed CK7, AE1AE3, CK8/18, chromogranin, synaptophysin, CD56, calcitonin (patchy) and TTF-1 (minimal focal). Stains for neurofilament, CK20, CK5/6, p40, p63, SOX10, MART-1, EMA, CEA, ER/PR, GATA3, GCDFP, mammoglobin, PAX-8, CDX2, napsin, ERG and MCPyV proved negative. The histopathological diagnosis was of a large cell neuroendocrine carcinoma, probably metastatic. The patient underwent comprehensive clinical, laboratory and radiographic investigations and no underlying primary carcinoma was detected. During a 20-month follow-up period with an oncologist, the patient remains well and free of any apparent carcinoma. This suggests a primary large cell neuroendocrine carcinoma of skin. To date, 3 such cases have been reported in Japanese patients. This is the first in a Caucasian resident of North America.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".