Radiological progression of extremity soft tissue sarcoma following pre-operative radiotherapy predicts for poor survival
Bibliographic record
Abstract
Objectives: To determine if radiological response to pre-operative radiotherapy is related to oncologic outcome in patients with extremity soft tissue sarcomas (STSs). Methods: 309 patients with extremity STS who underwent pre-operative radiation and wide resection were identified from a prospective database. Pre- and post-radiation MRI scans were retrospectively reviewed. Radiological response was defined by the modified Response Evaluation Criteria in Solid Tumours. Local recurrence-free, metastasis-free (MFS) and overall survival (OS) were compared across response groups. Results: Tumour volume decreased in 106 patients (34.3%; PR - partial responders), remained stable in 97 (31.4%; SD - stable disease), increased in 106 (34.3%; PD - progressive disease). The PD group were older (p = 0.007), had more upper extremity (p = 0.03) and high-grade tumours (p < 0.001). 81% of myxoid liposarcomas showed substantial decrease in size. There was no difference in initial tumour diameter (p = 0.5), type of surgery (p = 0.5), margin status (p = 0.4), or complications (p = 0.8) between the three groups. There were 10 (3.2%) local recurrences with no differences between the three response groups (p = 0.06). 5-year MFS was 52.1% for the PD group vs 73.8 and 78.5% for the PR and SD groups, respectively (p < 0.001). OS was similar (p < 0.001). Following multivariable analysis, worse MFS and OS were associated with higher grade, larger tumour size at diagnosis and tumour growth following pre-operative radiation. Older age was also associated with worse OS. Conclusion: STS that enlarge according to Response Evaluation Criteria in Solid Tumour criteria following pre-operative radiotherapy identify a high risk group of patients with worse systemic outcomes but equivalent local control. Advances in knowledge: Post-radiation therapy, STS enlargement may identify patients with potential for worse systemic outcomes but equivalent local control. Therefore, adjunct therapeutic approaches could be considered in these patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".