Endometrial Cancer Molecular Risk Stratification is Equally Prognostic for Endometrioid Ovarian Carcinoma
Bibliographic record
Abstract
PURPOSE: Endometrioid ovarian carcinoma (ENOC) is generally associated with a more favorable prognosis compared with other ovarian carcinomas. Nonetheless, current patient treatment continues to follow a "one-size-fits-all" approach. Even though tumor staging offers stratification, personalized treatments remain elusive. As ENOC shares many clinical and molecular features with its endometrial counterpart, we sought to investigate The Cancer Genome Atlas-inspired endometrial carcinoma (EC) molecular subtyping in a cohort of ENOC. EXPERIMENTAL DESIGN: mutant (POLEmut), moderate-risk mismatch repair deficient (MMRd), high-risk p53 abnormal (p53abn), and moderate-risk with no specific molecular profile (NSMP). Survival analysis with established clinicopathologic and subtype-specific features was performed. RESULTS: < 0.001) and survival similar to observations in EC. Median OS was 18.1 years in NSMP, 12.3 years in MMRd, 4.7 years in p53abn, and not reached for POLEmut cases. Subtypes were independent of stage, grade, and residual disease in multivariate analysis. CONCLUSIONS: EC-inspired molecular classification provides independent prognostic information in ENOC. Our findings support investigating molecular subtype-specific management recommendations for patients with ENOC; for example, subtypes may provide guidance when fertility-sparing treatment is desired. Similarities between ENOC and EC suggest that patients with ENOC may benefit from management strategies applied to EC and the opportunity to study those in umbrella trials.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| 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) | 0.002 | 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".