Are Uterine Risk Factors More Important Than Nodal Status in Predicting Survival in Endometrial Cancer?
Bibliographic record
Abstract
OBJECTIVE: To evaluate factors associated with survival after lymphadenectomy for endometrial cancer and to address their effect relating to systemic therapy. METHODS: This was a retrospective, population-based cohort study of 316 women with endometrial cancer who underwent surgery including lymphadenectomy in Ontario, Canada, from 1996-2000. Data obtained from administrative databases included comorbidities, socioeconomic status, grade, myometrial invasion, cervical involvement, lymphovascular-space invasion, nodal status, and adjuvant pelvic radiotherapy. Primary outcome was 5-year overall survival. Factors associated with survival were identified in a multivariable Cox proportional hazards model. RESULTS: Mean age was 62.2 years (+/-11.6 years). Thirty-eight women (12%) had positive pelvic nodes. Seventy-five (23.7%) received adjuvant pelvic radiotherapy. Age older than 60, grade 3 tumor, deep myometrial invasion (greater than 50%), and cervical stromal involvement were associated with a higher risk of death compared with reference categories. There were no survival differences according to comorbidities, socioeconomic status, or lymphovascular-space invasion. Five-year overall survival was 53.1% for node-negative patients with two or three uterine risk factors and 75.0% for node-positive patients with none or only one uterine risk factor. Pelvic-node status was not an independent determinant of survival (positive nodes: hazard ratio 1.39, 95% confidence interval 0.89-2.18). CONCLUSION: High-risk uterine factors including grade 3 tumor, deep myometrial invasion, and cervical stromal involvement are more significant determinants of survival in endometrial cancer than pelvic-node status. Uterine risk factors should be considered, regardless of nodal status, when offering systemic therapy to maximize survival outcomes. LEVEL OF EVIDENCE: II.
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How this classification was reachedexpand
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".