Textbook Outcomes for Retroperitoneal Sarcoma Resection: A Multi-Centre Review
Bibliographic record
Abstract
For patients with retroperitoneal sarcomas (RPSs), en-bloc resection with macroscopically negative margins remains the only potentially curative treatment. Textbook outcomes (TOs) are composite measures developed to compare ideal surgical outcomes for complex oncologic resections. The aims of this study were as follows: to define TO for RPS resections; to investigate the impact of treating service and other variables on TO; and to investigate the impact of treating service on achieving a TO. Population-based data from the Queensland Oncology Repository (QOR) was used to perform a retrospective review of all adult patients who underwent resection for primary RPS in Queensland between 2012 and 2022. TO was defined as follows: en-bloc resection; macroscopically negative margins; no unplanned ICU admission, no Clavien–Dindo III or greater complications; hospital length of stay of 14 days or less; no readmission within 30 days; and no 90-day mortality. A TO was achieved in 82 (56.94%) of the 144 patients included in the study. A high-grade histological subtype, the resection of three or more contiguous organs, major vascular resection and treatment outside of a high-volume sarcoma centre (HVSC) were significant negative predictors of achieving TOs (p < 0.05). On multivariate analysis, treatment at a high-volume sarcoma centre was independently associated with a 2.6-fold increase in TO (1.18–5.88, p = 0.02). Achieving a TO was associated with higher five-year DFS (61.5% vs. 41.3%, p = 0.03) and OS (76% vs. 59.4%, p = 0.02). In our state, TOs provide a measure of the quality of RPS resection across multiple health services, with patients treated at high-volume sarcoma centres more likely to achieve a TO. TO rates are associated with improved five-year DFS and OS.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".