Cutaneous Leiomyosarcoma: A SEER Database Analysis
Bibliographic record
Abstract
BACKGROUND: Cutaneous leiomyosarcoma is a rare dermal neoplasm usually arising from the pilar smooth muscle. It is considered a relatively indolent neoplasm, and there is debate whether designation as sarcoma is appropriate. Owing to some conflicting data in the literature, however, its behavior warrants further clarification. OBJECTIVE: To determine the clinical behavior and demographic and pathologic characteristics of cutaneous leiomyosarcoma. MATERIALS AND METHODS: The Surveillance, Epidemiology and End Results database was used to collect data on cutaneous leiomyosarcoma and 2 reference populations: cutaneous angiosarcoma (aggressive) and atypical fibroxanthoma (indolent). Demographic and oncologic characteristics were examined, and overall survivals (OS) and disease-specific survivals were compared. RESULTS: Leiomyosarcoma and atypical fibroxanthoma displayed lower stage (localized: 69.7% and 66.8% respectively), smaller size (<3 cm: 90.5% and 72%), and lower rates of disease-specific mortality (2.9% and 7.8%) compared with angiosarcoma. Patients with leiomyosarcoma had a 5-year disease-specific survival rate of 98% and OS rate of 85%. CONCLUSION: Cutaneous leiomyosarcoma shows outcomes similar to atypical fibroxanthoma. It is nearly always indolent and should be distinguished from more aggressive cutaneous and subcutaneous sarcomas. Clear communication of the biologic potential may be best achieved using alternate diagnostic terminology such as "atypical intradermal smooth-muscle neoplasm."
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".