Stage IIIC Endometrial Cancer
Bibliographic record
Abstract
PURPOSE: The optimal radiation (RT) volume for node-positive endometrial cancer is controversial. This study evaluates clinical outcomes in patients with stage IIIC, N1 endometrial cancer who received RT to the pelvis (PV RT) or pelvis plus para-aortic nodes (PV-PAN RT). METHODS: Overall, there were 89 women with stage IIIC endometrial cancer. Of these, 57 women had N1-only disease, forming the study cohort. Clinicopathologic characteristics, recurrence rates, endometrial cancer-specific survival (ECSS), and overall survival (OS) were examined among patients treated with pelvic RT (n=23) compared with pelvic plus para-aortic RT (n=34). Multivariable analysis of ECSS and OS was performed using Cox regression modeling. RESULTS: Median follow-up was 5.1 years. Adjuvant chemotherapy was used in 51/57 (89%) of N1 cases. Women with N1 disease who received PV-PAN RT compared with PV RT experienced lower recurrence (26% vs. 52%, P=0.06) and higher survival rates (5 y ECSS 81.5% vs. 47.0%, P=0.04 and OS 79.1% vs. 47.0%, P=0.01). On multivariable analysis, RT volume was not significantly associated with OS, whereas chemotherapy was associated with improved ECSS and OS. CONCLUSIONS: RT conferred excellent local control, whereas chemotherapy was associated with improved survival in women with N1 endometrial cancer. Distant relapse remains the most common site of recurrence despite chemotherapy.
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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 | 0.001 |
| 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) | 0.002 | 0.001 |
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".