Does mismatch repair (MMR) deficiency have prognostic significance in low-risk endometrioid endometrial cancers?
Bibliographic record
Abstract
e17122 Background: Mismatch repair (MMR) deficiency is observed in 25-30% of all endometrial cancers. This can be detected by the absence of MMR protein staining on immunohistochemistry (IHC), and is used in many jurisdictions as a screen for an inherited mutation in one of the MMR genes (Lynch Syndrome). Only 10% of women with MMR deficiency (MMRd) have Lynch syndrome, but MMRd may still have prognostic significance. The objective of this study was to compare clinical outcomes between MMR deficient and proficient low-risk endometrioid endometrial cancers (stage IA, grade 1/2). Methods: This was a retrospective population-based cohort study of all low-risk endometrial cancers from Vancouver Coastal Health authority region from 2011 to 2016 that were assessed for MMR deficiency (MMRd). Primary outcome measures were recurrence rates expressed per person-years (py), progression free survival (PFS) and overall survival (OS) calculated using Kaplan-Meier method and log-rank tests. Cox proportional hazards model estimated the association between MMRd and recurrence and death after adjustment for covariates, expressed as hazard ratios (HR). Results: There were 475 low-risk patients, including 131 MMRd (27.6%) and 345 MMRp (proficient) patients. Women with MMRd tumors had higher recurrence rates (3.53p100py vs 1.21p100py) and worse PFS (p = 0.0082) compared to women with MMRp tumors. After adjustment for age, LVSI status, adjuvant therapy, and post-operative grade, MMRd status remained associated with a higher risk of recurrence (HR 2.99, 95% CI 1.27-7.04). There was no significant difference in OS between MMR groups (HR 1.38, 95% CI 0.57-3.33). Conclusions: In low-risk stage IA grade 1 or 2 endometrioid endometrial cancers, MMR deficiency is associated with a higher recurrence rate than in MMR proficient cases, after adjustment for covariates, implying that MMR deficiency reflects a different biology in endometrial cancer.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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 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".