Interobserver Agreement in Endometrial Carcinoma Histotype Diagnosis Varies Depending on The Cancer Genome Atlas (TCGA)-based Molecular Subgroup
Bibliographic record
Abstract
The Cancer Genome Atlas recently identified a genomic-based molecular classification of endometrial carcinomas, with 4 molecular categories: (1) ultramutated (polymerase epsilon [POLE] mutated), (2) hypermutated (microsatellite instability), (3) copy number abnormalities-low, and (4) copy number abnormalities-high. Two studies have since proposed models to classify endometrial carcinomas into 4 molecular subgroups, modeled after The Cancer Genome Atlas, using simplified and more clinically applicable surrogate methodologies. In our study, 151 endometrial carcinomas were molecularly categorized using sequencing for the exonuclease domain mutations (EDM) of POLE, and immunohistochemistry for p53 and mismatch repair (MMR) proteins. This separated cases into 1 of 4 groups: (1) POLE EDM, (2) MMR-D, (3) p53 wildtype (p53 wt), or (4) p53 abnormal (p53 abn). Seven gynecologic pathologists were asked to assign each case to one of the following categories: grade 1 to 2 endometrioid carcinoma (EC), grade 3 EC, mucinous, serous carcinoma (SC), clear cell, dedifferentiated, carcinosarcoma, mixed, and other. Consensus diagnosis among all 7 pathologists was highest in the p53 wt group (37/41, 90%), lowest in the p53 abn group (14/36, 39%), and intermediate in the POLE EDM (22/34, 65%) and MMR-D groups (23/40, 58%). Although the majority of p53 wt endometrial carcinomas are grade 1 to 2 EC (sensitivity: 90%), fewer than half of grade 1 to 2 EC fell into the p53 wt category (positive predictive value: 42%). Pure SC almost always resided in the p53 abn group (positive predictive value: 96%), but it was insensitive as a marker of p53 abn (sensitivity 64%) and the reproducibility of diagnosing SC was suboptimal. The limitations in the precise histologic classification of endometrial carcinomas highlights the importance of an ancillary molecular-based classification scheme.
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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 | 0.037 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".