Physical activity and the risk of colorectal cancer in Lynch syndrome
Bibliographic record
Abstract
Greater physical activity is associated with a decrease in risk of colorectal cancer for the general population; however, little is known about its relationship with colorectal cancer risk in people with Lynch syndrome, carriers of inherited pathogenic mutations in genes affecting DNA mismatch repair (MMR). We studied a cohort of 2,042 MMR gene mutations carriers (n = 807, diagnosed with colorectal cancer), from the Colon Cancer Family Registry. Self-reported physical activity in three age-periods (20-29, 30-49 and ≥50 years) was summarized as average metabolic equivalent of task hours per week (MET-hr/week) during the age-period of cancer diagnosis or censoring (near-term exposure) and across all age-periods preceding cancer diagnosis or censoring (long-term exposure). Weighted Cox regression was used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) for the association between physical activity and colorectal cancer risk. Near-term physical activity was associated with a small reduction in the risk of colorectal cancer (HR ≥35 vs. <3.5 MET-hr/week, 0.71; 95% CI, 0.53-0.96). The strength and direction of associations were similar for long-term physical activity, although the associations were not nominally significant. Our results suggest that physical activity is inversely associated with the risk of colorectal cancer for people with Lynch syndrome; however, further confirmation is warranted. The potential modifying effect of physical activity on colorectal cancer risk in people with Lynch syndrome could be useful for risk prediction and support counseling advice for lifestyle modification to reduce cancer risk.
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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 | 0.001 |
| 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".