Pilomatrix Carcinoma: Report of Two Cases of the Head and Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Pilomatrix carcinoma (PC) is a rare skin tumor arising from hair follicle matrix cells. It is locally aggressive with a high rate of local recurrence after surgical excision. Few cases in the literature have been described and the management is not well defined. OBJECTIVES: The aim of this study was to present two cases of PC located on the head and review the relevant literature about epidemiology, clinical and dermoscopic evaluation, characteristics of local and distant metastases, local recurrence rate and management of this rare skin tumor. METHODS: We consulted databases from PubMed, Research Gate and Google Scholar, from January 2012 to November 2022. We reviewed the literature and reported two additional cases. RESULTS: We selected 52 tumors in middle-aged to older patients located mostly on the head. Dermoscopy evaluation was rarely performed in the pre-operative diagnostic setting. The most definitive treatment was wide local excision, but local recurrences were common. In total, we observed 11 cases of recurrences and 9 patients with locoregional or distant metastases. Four patients received adjuvant radiotherapy, two patients needed chemotherapy and local cancer therapy and one patient received radiochemotherapy. CONCLUSION: Our reports and the review of the literature can provide a better awareness and management of this rare tumor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".