Patterns of recurrence and survival probability after second recurrence of retroperitoneal sarcoma: A study from TARPSWG
Bibliographic record
Abstract
BACKGROUND: In this series from the Transatlantic Australasian Retroperitoneal Sarcoma Working Group (TARPSWG), the authors examined longitudinal outcomes of patients with a second recurrence of retroperitoneal sarcoma (RPS) after complete resection of a first local recurrence (LR). METHODS: Data from patients undergoing resection of a first LR from January 2002 to December 2011were collected from 22 sarcoma centers. The primary outcome was overall survival (OS) after second recurrence. RESULTS: Second recurrences occurred in 400 of 567 patients (70.5%) after an R0/R1 resection of a first locally recurrent RPS. Patterns of disease recurrence were LR in 323 patients (80.75%), distant metastases (DM) in 55 patients (13.75%), and both LR and DM in 22 patients (5.5%). The main subtype among the LR group was liposarcoma (77%), whereas DM mainly were leiomyosarcomas (43.6%). In patients with a second LR only, a total of 200 patients underwent re-resection (61.9%). The 5-year OS rate varied significantly based on the pattern of failure (P < .001): 45.6% for the LR group, 25.5% for the DM group, and 0% for the group with LR and DM. The only factors found to be associated with improved OS on multivariable analysis were both time between second surgery and the development of the second recurrence (32 months vs 8 months: hazard ratio, 0.44 [P < .001]) and surgery for second recurrence (yes vs no: hazard ratio, 3.25 [P < .001]). The 5-year OS rate for patients undergoing surgery for a second LR was 59% versus 18% in the patients not deemed suitable for surgical resection. CONCLUSIONS: Survival rates after second recurrence of RPS varied based on patterns of disease recurrence and treatment. Durable disease-free survivors were identified after surgery for second LR in patients selected for this intervention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".