Case–control study of lifetime alcohol consumption and endometrial cancer risk
Bibliographic record
Abstract
PURPOSE: Alcohol consumption is hypothesized to increase the risk of endometrial cancer by increasing circulating estrogen levels. This study sought to investigate the association between lifetime alcohol consumption and endometrial cancer risk. METHODS: We recruited 514 incident endometrial cancer cases and 962 frequency age-matched controls in this population-based case-control study in Alberta, Canada, from 2002 to 2006. Participants completed in-person interviews querying lifetime alcohol consumption and other relevant health and lifestyle factors. Participants reported the usual number of drinks of beer, wine, and liquor consumed; this information was compiled for each drinking pattern reported over the lifetime to estimate average lifetime exposure to alcohol. RESULTS: Lifetime average alcohol consumption was relatively low (median intake: 3.9 g/day for cases, 4.9 g/day for controls). Compared with lifetime abstainers, women consuming >2.68 and ≤8.04 g/day alcohol and >8.04 g/day alcohol on average over the lifetime showed 38 and 35 % lower risks of endometrial cancer, respectively (p trend = 0.023). In addition, average lifetime consumption of all types of alcohol was associated with decreased risks. There was no evidence for effect modification by body mass index, physical activity, menopausal status, and hormone replacement therapy use combined and effects did not differ by type of endometrial cancer (type I or II). CONCLUSION: This study provides epidemiologic evidence for an inverse association between relatively modest lifetime average alcohol consumption (approximately 1/4 to 1/2 drink/day) and endometrial cancer risk. The direction of this relation is consistent with previous studies that examined similar levels of alcohol intake.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".