Endometrial carcinoma: molecular subtypes, precursors and the role of pathology in early diagnosis
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
Endometrial carcinoma (EC) is classified into a wide range of morphological variants; this list has expanded over the past decade with the inclusion of mesonephric-like and dedifferentiated carcinoma as EC variants in the fifth edition of the WHO Classification of Female Genital Tumours, and recognition that carcinosarcoma is a biphasic carcinoma rather than a sarcoma. Each EC variant has distinct molecular abnormalities, including TCGA-based molecular subtypes, allowing further subclassification and adding complexity. In contrast to this rapid progress in understanding EC, there are only two recognized EC precursor lesions: endometrial atypical hyperplasia/endometrioid intraepithelial neoplasia (EAH/EIN) and serous intraepithelial carcinoma, a situation that has not changed for many years. Diagnosis of EC precursors is a cornerstone of surgical pathology practice, with early diagnosis contributing to the relatively favorable prognosis of EC. In this review we relate the precursor lesions to each of the EC morphological variants and molecular subtypes, discuss how successful early diagnosis is for each variant/molecular subtype and how it might be improved, and identify knowledge gaps where there is insufficient understanding of EC histogenesis. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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