Histological features associated with occult lymph node metastasis in <scp>FIGO</scp> clinical stage <scp>I</scp>, grade <scp>I</scp> endometrioid carcinoma
Bibliographic record
Abstract
AIMS: Lymph node involvement affects prognosis/treatment in endometrial carcinoma patients. We assessed various histological features associated with nodal metastasis in patients with grade I, stage I endometrial endometrioid carcinoma (EEC). METHODS AND RESULTS: Eighteen stage I EECs with occult positive lymph nodes and 36 controls were assessed for depth of myoinvasion; microcystic, elongated and fragmented (MELF) pattern of myometrial invasion; lymphovascular invasion (LVI); and epithelial metaplasia. Nodal metastases were subclassified as isolated tumour cells (ITCs; ≤0.2 mm), micrometastasis (>0.2 mm and <2 mm), or macrometastasis (≥2 mm). Node-positive cases had significantly higher rates of LVI (P < 0.001) and MELF invasion (P = 0.003) on univariate analysis. Only LVI was associated significantly with nodal metastasis on multivariate analysis (P = 0.002). Tumours with MELF invasion demonstrated reduced E-cadherin expression. Macrometastases were identified in seven cases (39%) with or without micrometastasis/ITCs. Eight (44%) contained only ITCs. Eleven (61%) had histiocyte-like nodal metastases. Biopsy material from four of six (67%) and five of 17 (29%) cases with and without nodal metastasis showed detached eosinophilic tumour cell buds. Of the former, three were associated with histiocyte-like nodal metastases - a feature absent in biopsies without tumour budding. CONCLUSIONS: Lymph nodes from grade I EEC exhibiting cellular budding or LVI should be examined for occult metastases, especially in the form of histiocyte-like cells.
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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 | 0.001 | 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) | 0.001 | 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".