Cancer Risks for<i>MLH</i><i>1</i>and<i>MSH</i><i>2</i>Mutation Carriers
Bibliographic record
Abstract
We studied 17,576 members of 166 MLH1 and 224 MSH2 mutation-carrying families from the Colon Cancer Family Registry. Average cumulative risks of colorectal cancer (CRC), endometrial cancer (EC), and other cancers for carriers were estimated using modified segregation analysis conditioned on ascertainment criteria. Heterogeneity in risks was investigated using a polygenic risk modifier. Average CRC cumulative risks at the age of 70 years (95% confidence intervals) for MLH1 and MSH2 mutation carriers, respectively, were estimated to be 34% (25%-50%) and 47% (36%-60%) for male carriers and 36% (25%-51%) and 37% (27%-50%) for female carriers. Corresponding EC risks were 18% (9.1%-34%) and 30% (18%-45%). A high level of CRC risk heterogeneity was observed (P < 0.001), with cumulative risks at the age of 70 years estimated to follow U-shaped distributions. For example, 17% of male MSH2 mutation carriers have estimated lifetime risks of 0%-10% and 18% have risks of 90%-100%. Therefore, average risks are similar for the two genes but there is so much individual variation about the average that large proportions of carriers have either very low or very high lifetime cancer risks. Our estimates of CRC and EC cumulative risks for MLH1 and MSH2 mutation carriers are the most precise currently available.
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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 | 0.004 |
| 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 | 0.000 | 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".