Phase 2 Southwest Oncology Group‐directed intergroup trial (S0505) of sorafenib in advanced soft tissue sarcomas
Bibliographic record
Abstract
BACKGROUND: Patients with advanced soft tissue sarcomas (STS) have limited therapeutic options. Sorafenib (BAY 43-9006) is a multitargeted tyrosine kinase inhibitor of raf, vascular endothelial growth factor receptors 1 (VEGFR1) through 3, platelet-derived growth factor B, fms-like tyrosine kinase 3, and c-kit, and some of these may be relevant in STS. METHODS: The authors tested sorafenib at a dose of 400 mg twice daily in patients with advanced vascular sarcoma (VS), high-grade liposarcomas, and leiomyosarcomas who had received 0 or 1 previous regimens for advanced disease. RESULTS: Fifty-one patients were accrued to the study, and 37 were evaluable for toxicity and response. There were no unexpected side effects and no confirmed responses. The median progression-free survival was 3 months, and the median overall survival was 17 months. Six of 8 patients in the VS cohort had prolonged clinical benefit (stable disease or better), resulting in a median progression-free survival of 5 months compared with 2 to 3 months for the patients who had liposarcoma and leiomyosarcomas. CONCLUSIONS: Sorafenib at the dose and schedule studied did not result in any responses in the VS, liposarcoma, or leiomyosarcoma cohort according to Response Evaluation Criteria in Solid Tumors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".