Local control following resection of primary retroperitoneal sarcoma with and without preoperative radiotherapy.
Bibliographic record
Abstract
10572 Background: Retroperitoneal sarcoma (RPS) represents a therapeutic challenge due to its typically advanced stage at presentation, with local failure a harbinger of death from sarcoma following resection of primary RPS. Preoperative external beam radiotherapy (Pre-op RT) offers the potential for sterilization of margins and better local control. We present mature outcomes according to histologic subtype and treatment of patients with primary RPS managed at our center. Methods: All patients presenting with primary RPS between 01/96 and 06/11 identified from a prospective database were eligible. Distant metastases or unresectability at presentation, receipt of pre-op chemotherapy or post-op radiotherapy were exclusion criteria. All biopsy and resection specimens were re-analysed by an expert pathologist and mdm2 status used to facilitate histologic subtyping. Cumulative-incident rate curves were constructed for local and distant recurrence (LR, DR). Results: All 120 included patients underwent total gross resection. In this cohort, overall survival was 75% and 64% at 5 and 10 yrs, median 206 mos, and disease specific survival was 85% and 76% at 5 and 10 yrs, median 209 mos. Pre-op RT was given to 101 patients while 19 had surgery alone. Surgical approach, histologic subtype (80% liposarcoma, LPS) and follow-up (median 59 mos) did not differ between treatment groups; median size was larger (28 vs. 19 cm) and histologic grade lower in the surgery alone group. For the 120 patients, DR occured in 12 at a median 23 mos (range 2-131) postoperatively and varied significantly by histology (4/65 DD-LPS; 0/31 WD-LPS; 7/17 LMS; 1/7 other; p < 0.01), but not treatment group. LR occured in 24 at a median 22.5 mos (range 2-103) and varied significantly by histology (22/65 DD-LPS; 2/31 WD-LPS; 0/24 other; p = 0.01). For the entire cohort, LR rate was 20% and 28% at 5 and 10 yrs. LR at 5 yrs varied significantly by treatment group (16% for pre-op RT, 51% for surgery alone, p < 0.01). Conclusions: Pre-op RT was associated with improved local control compared with a contemporaneous control. Participation in the EORTC randomized trial of pre-opRT vs. surgery alone is essential to determine the true benefit of pre-op RT in primary RPS.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".