Pediatric Undifferentiated Sarcoma of the Soft Tissues: A Clinicopathologic Study
Bibliographic record
Abstract
Pediatric undifferentiated soft tissue sarcomas represent a major challenge for pathologists and clinicians. The goal of this study was to identify cases that warranted this diagnosis by current standards of analysis and then determine if there are clinicopathological commonalities that may be useful for diagnosis, management, and prognosis. Eighteen potential patients were identified using the institutional pathology database. Three cases were reclassified as specific sarcomas, and 2 cases had insufficient material for molecular analysis, leaving 13 cases for pathological review and 12 patients for radiological and clinical review. There were 7 males and 6 females. The median age at diagnosis was 11 years (1 month to 16 years). Tumors commonly involved the trunk (7 of 13; 54%) and ranged in size from 1.7 to 14.5 cm (mean, 6.7 cm). Eleven patients received ifosfamide/etoposide chemotherapy and 4 received irradiation. Five-year event-free and overall survival (EFS and OS) rates were 54% and 74%, respectively. The predominant histological pattern was round to plump spindled cells forming sheets (9 of 13; 69%) and severe atypia was associated with decreased survival (P = 0.048). Immunohistochemistry showed positivity for vimentin (92%), CD117 (92%), and vascular endothelial growth factor (69%), and 8% to 23% showed focal positivity for epithelial, neural, or myogenic markers. Tumors were uniformly negative for translocations associated with pediatric sarcomas. The presence of certain common morphological and immunohistochemical features in the absence of specific molecular genetic abnormalities allows for a diagnosis of pediatric undifferentiated soft tissue sarcoma; however, whether this group of neoplasms forms a unique category of tumors or a common precursor pathway for a number of different sarcomas awaits further study.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".