Serum CA125 levels in the context of ProMisE molecular classification provides pre-operative prognostic information that can direct endometrial cancer management
Bibliographic record
Abstract
OBJECTIVE: Previous research suggests serum CA125 reflects extra-uterine disease in patients with endometrial carcinoma (EC). Our objective was to determine if CA125 can identify patients with extra-uterine and/or nodal metastases, the association of this biomarker with EC molecular subtype, and to explore an optimal cutoff in this context. METHODS: We assessed the association of CA125 levels with clinicopathologic and outcomes data on a cohort of 1107 molecularly classified EC. RESULTS: Abnormal CA125 (>35kU/L) was associated with higher stage and lymph node metastases (LNM) in all EC and in each molecular subtype on univariate (p < 0.01) and multivariate (p < 0.05) analyses. POLEmut had the lowest median CA125 level and proportion of CA125 abnormal patients, and p53abn the highest proportion (p < 0.001). CA125 > 35 kU/L had a sensitivity of 0.82, specificity 0.53, positive-predictive-value 0.92, and negative-predictive-value 0.31 for LNM, with similar values for stage>I. CA125 > 35 kU/L was associated with worse overall (OS), disease-specific (DSS), and progression-free survival (PFS) in all EC, p53abn (OS, DSS, PFS), NSMP (OS, DSS), and MMRd (OS, DSS) subtypes. CA125 > 35 kU/L demonstrated a relative risk (RR) of 2.50 with presence of stage III/IV disease (p < 0.001) and RR 18.4 for the presence of synchronous endometrial and ovarian carcinomas (SEOC)/co-existing adnexal malignancies (CAM) (p < 0.001). An exploratory cut point, optimized for correlation with DSS (CA125 > 24 kU/L) show similar association with clinical parameters and survival outcome. CONCLUSIONS: CA125 levels are associated with molecular subtype, stage>I disease, and SEOC/CAM. CA125 remains a useful clinical tool in the triage of EC in the era of molecular classification.
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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 | 0.002 |
| 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".