Gallstones and incident colorectal cancer in a large pan‐European cohort study
Bibliographic record
Abstract
Gallstones, a common gastrointestinal condition, can lead to several digestive complications and can result in inflammation. Risk factors for gallstones include obesity, diabetes, smoking and physical inactivity, all of which are known risk factors for colorectal cancer (CRC), as is inflammation. However, it is unclear whether gallstones are a risk factor for CRC. We examined the association between history of gallstones and CRC in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a prospective cohort of over half a million participants from ten European countries. History of gallstones was assessed at baseline using a self-reported questionnaire. The analytic cohort included 334,986 participants; a history of gallstones was reported by 3,917 men and 19,836 women, and incident CRC was diagnosed among 1,832 men and 2,178 women (mean follow-up: 13.6 years). Hazard ratios (HR) and 95% confidence intervals (CI) for the association between gallstones and CRC were estimated using Cox proportional hazards regression models, stratified by sex, study centre and age at recruitment. The models were adjusted for body mass index, diabetes, alcohol intake and physical activity. A positive, marginally significant association was detected between gallstones and CRC among women in multivariable analyses (HR = 1.14, 95%CI 0.99-1.31, p = 0.077). The relationship between gallstones and CRC among men was inverse but not significant (HR = 0.81, 95%CI 0.63-1.04, p = 0.10). Additional adjustment for details of reproductive history or waist circumference yielded minimal changes to the observed associations. Further research is required to confirm the nature of the association between gallstones and CRC by sex.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".