The effect of the setting of a positive surgical margin in soft tissue sarcoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The objectives of this study were to evaluate the risk of local recurrence and survival after soft tissue sarcoma (STS) resection with positive margins and to evaluate the safety of sparing adjacent critical structures. METHODS: One hundred sixty-nine patients with localized STS who had positive resection margins were identified from a prospective database. Patients who had positive margins were stratified into 3 groups, each representing a specific clinical scenario: critical structure positive margin (eg major nerve, vessel, or bone), tumor bed resection positive margin, and unexpected positive margin. The rates of local recurrence-free survival (LRFS) and cause-specific survival (CSS) were calculated and compared with relevant control patients who had negative margins after STS resection. RESULTS: After planned close dissection to preserve critical structures, the 5-year LRFS and CSS rates both depended on the quality of the surgical margins (97% and 80.3%, respectively, for those with negative margins vs 85.4% and 59.4%, respectively, for those with positive margins; P = .015 and P = .05, respectively). Negative margins achieved through resection of critical structures because of tumor invasion or encasement only slightly improved the 5-year rates of LRFS (91.2%) and CSS (63.6%; P = .8 and P = .9, respectively). The lowest 5-year LRFS and CSS rates were 63.4% and 59.2%, respectively, after an unexpected positive margin during primary surgery. CONCLUSIONS: After patients undergo resection of STS with positive margins, oncologic outcomes can be predicted based on the clinical context. Sparing adjacent critical structures in this setting is safe and contributes to improved functional outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it