Assessment of a Polygenic Risk Score for Colorectal Cancer to Predict Risk of Lynch Syndrome Colorectal Cancer
Bibliographic record
Abstract
Abstract It was not known whether the polygenic risk scores (PRSs) that predict colorectal cancer could predict colorectal cancer for people with inherited pathogenic variants in DNA mismatch repair genes—people with Lynch syndrome. We tested a PRS comprising 107 established single-nucleotide polymorphisms associated with colorectal cancer in European populations for 826 European-descent carriers of pathogenic variants in DNA mismatch repair genes (293 MLH1, 314 MSH2, 126 MSH6, 71 PMS2, and 22 EPCAM) from the Colon Cancer Family Registry, of whom 504 had colorectal cancer. There was no evidence of an association between the PRS and colorectal cancer risk, irrespective of which DNA mismatch repair gene was mutated, or sex (all 2-sided P > .05). The hazard ratio per standard deviation of the PRS for colorectal cancer was 0.97 (95% confidence interval = 0.88 to 1.06; 2-sided P = .51). Whereas PRSs are predictive of colorectal cancer in the general population, they do not predict Lynch syndrome colorectal 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".