Postoperative Morbidity After Radical Resection of Primary Retroperitoneal Sarcoma
Bibliographic record
Abstract
OBJECTIVE: To investigate the safety of radical resection for retroperitoneal sarcoma (RPS). BACKGROUND: The surgical management of RPS frequently involves complex multivisceral resection. Improved oncologic outcomes have been demonstrated with this approach compared to marginal excision, but the safety of radical resection has not been shown in a large study population. METHODS: The Transatlantic Retroperitoneal Sarcoma Working Group (TARPSWG) is an international collaborative of sarcoma centers. A combined experience of 1007 consecutive resections for primary RPS from January 2002 to December 2011 was studied retrospectively with respect to adverse events. A weighted organ score was devised to account for differences in surgical complexity. Univariate and multivariate logistic regression analyses were performed to investigate associations between adverse events and number and patterns of organs resected. Associations between adverse events and overall survival, local recurrence, and distant metastases were investigated. RESULTS: Severe postoperative adverse events (Clavien-Dindo ≥3) occurred in 165 patients (16.4%) and 18 patients (1.8%) died within 30 days. Significant predictors of severe adverse events were age (P = 0.003), transfusion requirements (P < 0.001), and resected organ score (P = 0.042). Resections involving pancreaticoduodenectomy, major vascular resection, and splenectomy/pancreatectomy were found to entail higher operative risk (odds ratio >1.5). There was no impact of postoperative adverse events on overall survival, local recurrence, or distant metastases. CONCLUSIONS: A radical surgical approach to RPS is safe when carried out at a specialist sarcoma center. High-risk resections should be carefully considered on an individual basis and weighed against anticipated disease biology. There appears to be no association between surgical morbidity and long-term oncologic outcomes.
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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 | 0.004 |
| 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 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".