Predictors of Recurrence and Survival in Malignant Triton Tumours: A Case Report and Systematic Review
Bibliographic record
Abstract
Abstract 1.1 Introduction: Malignant triton tumours (MTTs) are a rare and aggressive subset of malignant peripheral nerve sheath tumours (MPNSTs). A systematic review was conducted to better understand the prognosis and prognostic factors of MTTs in adult patients, and provide treatment guidance for clinicians encountering this rare tumour. 1.2 Methods: A PubMed search was conducted using keywords: “rhabdomyoblastic,” “rhabdomyosarcomatous,” “triton,” “case series” and “case report”. Reference list search was also completed. Two independent investigators completed abstract and full-text reviews. Articles were restricted to peer-reviewed articles in English language only containing adult MTT cases (≥ 18 years), and excluding articles with insufficient treatment/outcome data. Univariable and multivariable Cox proportional hazards regression was performed to identify significant predictors of overall survival (OS) and progression-free survival (PFS). 1.3 Results: A total of 123 cases from the literature and 1 case from our institution were included in the final analysis. The 2-year and 5-year OS was 46.2% and 32.2%, and the 2-year and 5-year PFS was 27.1% and 21.3%, respectively. On multivariable analysis for OS, prior radiation exposure (hazard ratio [HR]: 3.99, p = 0.027), central nervous system or spine disease site (HR: 5.86, p < 0.001) and positive neurofibromatosis 1 (NF1) status (HR: 3.42, p < 0.001) were associated with worse survival. Adjuvant radiotherapy (HR: 0.58, p = 0.038) was associated with improved survival. Positive NF1 status (HR: 2.34, p < 0.001) and positive margins (HR: 3.28, p < 0.001) were associated with worse PFS. 1.4 Conclusions: MTTs are rare and have poor long-term survival. Negative surgical margins and adjuvant radiation were found to be associated with improved outcomes.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".