Morphologically high‐grade trichoblastic carcinoma: a clinicopathological study with long‐term clinical follow‐up
Bibliographic record
Abstract
AIMS: Trichoblastic carcinomas (malignant trichoblastomas) are rare and poorly documented neoplasms characterised by malignant transformation of a pre-existing benign trichoblastoma, and are subdivided histologically into low-grade and high-grade tumours. Whereas morphologically low-grade trichoblastic carcinomas show indolent behaviour, morphologically high-grade trichoblastic carcinomas have been associated with a poor prognosis, but little is known about their true biological potential. The aim of this study was to better define the clinicopathological features and outcomes of morphologically high-grade trichoblastic carcinomas. METHODS AND RESULTS: Four high-grade trichoblastic carcinomas were retrieved from departmental files, and the clinical and histopathological features and follow-up were recorded. The tumours presented as nodules on the scalps, necks and shoulders of adults (median age, 40 years; range, 30-55 years) with a female predominance of 3:1. Three patients had a longstanding history with recent change. Histologically, three tumours were characterised by an expansile cellular nodule composed of sheets of pleomorphic epithelioid cells with brisk mitotic activity and necrosis arising in a background of a benign trichoblastoma. One tumour showed a more gradual transition from a benign trichoepithelioma to an undifferentiated carcinoma with infiltrative growth and perineural infiltration. All patients were alive with no evidence of recurrence or metastasis following complete excision after a median follow-up of 96 months (range, 30-180 months). CONCLUSIONS: The correct diagnosis of high-grade trichoblastic carcinoma relies on adequate sampling and recognition of the benign trichoblastic precursor lesion, i.e. trichoblastoma or trichoepithelioma. Despite the concerning histological features of the malignant component, the tumours appear to be less aggressive than previously thought.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".