Post‐relapse outcomes after primary extended resection of retroperitoneal sarcoma: A report from the Trans‐Atlantic RPS Working Group
Bibliographic record
Abstract
BACKGROUND: Despite a radical surgical approach to primary retroperitoneal sarcoma (RPS), many patients experience locoregional and/or distant recurrence. The objective of this study was to analyze post-relapse outcomes for patients with RPS who had initially undergone surgical resection of their primary tumor at a specialist center. METHODS: All consecutive patients who underwent macroscopically complete resection for primary RPS at 8 high volume centers from January 2002 to December 2011 were identified, and those who developed local recurrence (LR) only, distant metastasis (DM) only, or synchronous local recurrence and distant metastasis (LR+DM) during the follow-up period were included. Overall survival (OS) was calculated for all groups, as was the crude cumulative incidence of a second recurrence after the first LR. Multivariate analyses for OS were performed. RESULTS: In an initial series of 1007 patients with primary RPS, 408 patients developed recurrent disease during the follow-up period. The median follow-up from the time of recurrence was 41 months. The median OS was 33 months after LR (n = 219), 25 months after DM (n = 146), and 12 months after LR+DM (n = 43), and the 5-year OS rates were 29%, 20%, and 14%, respectively. Predictors of OS after LR were the time interval to LR and resection of LR, while histologic grade approached significance. For DM, significant predictors of OS were the time interval to DM and histologic subtype. The subgroup of patients who underwent resection of recurrent disease had a longer median OS than patients who did not undergo resection. CONCLUSIONS: Relapse of RPS portends high disease-specific mortality. Patients with locally recurrent or metastatic disease should be considered for resection. Cancer 2017;123:1971-1978. © 2017 American Cancer Society.
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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 | 0.002 |
| 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".