Cancer risks for monoallelic <i>MUTYH</i> mutation carriers with a family history of colorectal cancer
Bibliographic record
Abstract
Cancer risks for a person who has inherited a MUTYH mutation from only one parent (monoallelic mutation carrier) are uncertain. Using the Colon Cancer Family Registry and Newfoundland Familial Colon Cancer Registry, we identified 2,179 first- and second-degree relatives of 144 incident colorectal cancer (CRC) cases who were monoallelic or biallelic mutation carriers ascertained by sampling population complete cancer registries in the United States, Canada and Australia. Using Cox regression weighted to adjust for sampling on family history, we estimated that the country-, age- and sex-specific standardized incidence ratios (SIRs) for monoallelic mutation carriers, compared to the general population, were: 2.04 (95% confidence interval, CI 1.56-2.70; p < 0.001) for CRC, 3.24 (95%CI 2.18-4.98; p < 0.001) for gastric cancer, 3.09 (95%CI 1.07-12.25; p = 0.07) for liver cancer and 2.33 (95%CI 1.18-5.08; p = 0.02) for endometrial cancer. Age-specific cumulative risks to age 70 years, estimated using the SIRs and US population incidences, were: for CRC, 6% (95%CI 5-8%) for men and 4% (95%CI 3-6%) for women; for gastric cancer, 2% (95%CI 1-3%) for men and 0.7% (95%CI 0.5-1%) for women; for liver cancer, 1% (95%CI 0.3-3%) for men and 0.3% (95%CI 0.1-1%) for women and for endometrial cancer, 4% (95%CI 2-8%). There was no evidence of increased risks for cancers of the brain, pancreas, kidney, lung, breast or prostate. Monoallelic MUTYH mutation carriers with a family history of CRC, such as those identified from screening multiple-case CRC families, are at increased risk of colorectal, gastric, endometrial and possibly liver cancers.
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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 | 0.000 |
| 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".