Bibliographic record
Abstract
PURPOSE OF REVIEW: The purpose of this review is to highlight recent findings in the diagnosis, biology, risk-stratification, and treatment of soft tissue sarcomas (STS) in children. RECENT FINDINGS: In rhabdomyosarcoma (RMS), FOXO1 fusion status has been confirmed as an important prognostic factor. Among fusion-negative RMS, TP53 and MYOD1 mutations and detectable circulating tumor DNA at diagnosis are associated with inferior event-free survival in intermediate-risk disease. Delayed primary excision is associated with a reduced risk of local failure whereas radiotherapy dose escalation in large tumors has not improved local control. Maintenance therapy with vinorelbine and oral cyclophosphamide following induction chemotherapy in the RMS2005 trial led to improved survival. In non-rhabdomyosarcoma soft tissue sarcomas, the addition of pazopanib, a multitargeted receptor tyrosine kinase inhibitor, to upfront therapy did not improve survival. Atezolizumab is approved for alveolar soft part sarcoma, larotrectinib for NTRK fusion-positive STS, and afamitresgene autoleucel remains under evaluation in children with synovial sarcoma. Encouraging early results have been reported with tazemetostat and immune checkpoint inhibitors in epithelioid sarcoma and trastuzumab in desmoplastic small round cell tumor, respectively. SUMMARY: Pediatric STS are rare and biologically heterogeneous. Genomic advances have refined risk stratification and uncovered therapeutic targets; further progress relies on international collaboration and trials.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".