Postoperative radiotherapy improves local control and survival in patients with uterine leiomyosarcoma
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: To examine the role of radiotherapy (RT) in uterine leiomyosarcomas (LMS) and to determine the patient population who may benefit from RT. METHODS: From 1998-2008, 69 patients with primary uterine LMS underwent hysterectomy with or without pelvic radiotherapy to a median dose of 45 Gy. Univariate analysis was performed using the Kaplan-Meier method and cumulative-incidence function, and multivariate analyses using Fine and Gray or Cox proportional hazard models. RESULTS: Following surgery, 32 out of 69 patients received RT. There was no evidence of any correlation between patient, disease and treatment characteristics and the use of RT. Median follow-up was 57 months. RT was associated with reduced local recurrence (3y LR 19% vs. 39%; Gray's p = 0.019) and improved overall survival (3y OS 69% vs. 35%; log-rank p = 0.025) on univariate analysis. Multivariate analysis demonstrated that RT reduced LR (HR: 0.28, CI: 0.11-0.69, p = 0.006) and increased OS (HR: 0.44, CI: 0.23-0.85, p = 0.014) independent of other clinical and pathologic factors. Positive surgical margins increased the odds of LR (HR: 5.6, CI: 2.3-13.4, p = 0.00012). Large tumor size and advanced stage (II-IV) were associated with the development of distant metastases and inferior OS. CONCLUSIONS: Postoperative pelvic RT reduces LR and improves OS of patients with uterine LMS.
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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