International Multicenter Retrospective Study From the Ultra-rare Sarcoma Working Group on Low-grade Fibromyxoid Sarcoma, Sclerosing Epithelioid Fibrosarcoma, and Hybrid Forms
Bibliographic record
Abstract
The aim of the study was to report the outcome of primary localized low-grade fibromyxoid sarcoma (LGFMS), sclerosing epithelioid fibrosarcoma (SEF), and hybrid LGFMS/SEF (H-LGFMS/SEF). Patients with primary localized LGFMS, SEF, or H-LGFMS/SEF, surgically treated with curative intent from January 2000 to September 2022, were enrolled from 14 countries and 27 institutions. Pathologic inclusion criteria were predefined by expert pathologists. The primary endpoint was overall survival (OS). Secondary endpoints were crude cumulative incidence (CCI) of local recurrence (LR), CCI of distant metastases (DM), and post-metastases OS (p-OS). Two hundred ninety-four patients (239 LGFMS, 32 SEF, and 23 H-LGFMS/SEF) were identified. At a median(m-) follow-up (FU) of 57.1 months, 12/294 patients died. The 5- and 10-year OS were 99.0% and 95.9% in LGFMS, 86.2% and 67.0% in SEF, and 84.8% and 84.8% in H-LGFMS/SEF, respectively. Predictors of worse OS included pathology, age at surgery, systemic therapy, and radiotherapy. LR developed in 13/294 (4.4%) patients. The observed m-time to LR was 10.7 months. The 5- and 10-yr CCI-LR were 4.7% in LGFMS and 6.6% in SEF, respectively. There were no LR events in H-LGFMS/SEF. The sole predictor of higher risk of LR was histology. DM developed in 23/294 (7.8%) patients. The observed m-time to DM was 28.2 months. The 5- and 10-yr CCI-DM were 1.3% and 2.7% in LGMFS, 29.9% and 57.7% in SEF, 48.9% and 48.9% in H-LGFMS/SEF, respectively. Predictors of higher risk of DM were histology, systemic therapy, and radiotherapy. Primary localized LGFMS treated with complete surgical resection has an excellent prognosis, while about 50% of H-LGFMS/SEF and SEF develop DM within 5 to 10 years. Very long-term FU is needed to understand absolute cure rates.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".