Clinical significance of isolated tumor cells and micrometastasis in low‐grade, stage I endometrial cancer
Bibliographic record
Abstract
Introduction Ultrastaging in endometrial cancer (EC) led to increased detection of isolated tumor cells (ITC, ≤0.2 mm) and micrometastases (MM, 0.2‐2 mm), with unclear effect on prognosis. Our aim was to characterize the impact of ITC and MM on the outcome of these patients. Methods Grade 1 to 2 stage I endometrioid EC patients with nodal ITC (n = 11) or MM (n = 12) between 2012 and 2018 were retrospectively compared to a matched group of lymph node negative (n = 18) patients based on age, body mass index, grade, myometrial invasion, and lymphovascular space invasion (LVI) status using propensity score analysis (1:1). Mann‐Whitney U tests were performed on continuous variables and χ2 tests on categorical variables. Progression‐free survival (PFS) was the main endpoint. Results All MM and 81% of ITC had LVI. More ITC/MM patients received RT and chemotherapy (91.7% vs 18.4%; 70.8% vs 4.5%, respectively; P < 0.01) without significant difference in treatment‐related toxicities (25% vs 27.3% grade 1%‐2% and 20.8% vs 9.1% grade 2‐3; P = 0.538) or PFS (29.2 vs 25 months; P = 0.828). Two distant recurrences occurred in MM patients after 2.5 years; one lung and one para‐aortic lymph node. Conclusion With adjuvant treatment, ITC/MM in otherwise well‐differentiated stage I endometrial cancer have similar outcomes to matched LN− 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".