MLH1 Methylation Testing as an Integral Component of Universal Endometrial Cancer Screening—A Critical Appraisal
Bibliographic record
Abstract
MLH1/PMS2 loss due to MLH1 promoter hypermethylation (MLH1-PHM) is the most common cause of mismatch repair (MMR) deficiency in endometrial cancer (EC). This study aimed to determine the proportion of MLH1-deficient EC with PHM, assess the impact of the reflex MLH1-PHM testing strategy, and evaluate the associated costs within the publicly funded Canadian healthcare system. In a cohort of 2504 EC samples, 534 (21.4%) exhibited dual MLH1/PMS2 loss, prompting MLH1-PHM testing. Among 418 cases with available testing results, 404 (96.7%) were MLH1-hypermethylated, while 14 (3.3%) were non-methylated. The incidence of MLH1 non-methylated cases in our cohort was 14/2504 (0.56%) of all ECs, underscoring the prevalence of hypermethylation-driven MLH1/PMS2 loss in ECs universally screened for MMR deficiency. Reflex MLH1-PHM testing incurs substantial costs and resource utilization. Assay cost is CAD 231.90 per case, amounting to CAD 123,834.60 for 534 cases, with 30 tests needed per additional candidate for MLH1 germline analysis (CAD 6957.00 per candidate). This raises a provocative question: can we assume that the majority of the MLH1-deficient ECs are due to PHM and forgo further testing in healthcare systems with finite resources? It is imperative to assess resource utilization efficiency and explore optimized approaches that encompass clinical correlation, family history and judicious utilization of methylation testing to ensure it is provided only to those who stand to benefit from it.
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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 | 0.049 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".