Association between coffee drinking and endometrial cancer risk: A meta‐analysis
Bibliographic record
Abstract
Abstract Aim Coffee drinking is considered as a risk factor of endometrial cancer (EC). Here, we conducted a meta‐analysis of observational study to evaluate the relationship between coffee drinking and the risk of EC. Methods The MEDLINE and EMBASE databases were searched until July 2018. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated using a random‐effects model. Results A total of 24 studies (12 case–control and 12 cohort studies) on coffee intake with 9833 incident cases of EC and 699 234 subjects were included in the meta‐analysis. The pooled RR of endometrial cancer for the highest versus the lowest categories of coffee intake was 0.71 (95% CI: 0.65–0.77; I 2 = 14%, p for heterogeneity = 0.26). By study design, the pooled RRs were 0.68 (95% CI: 0.56–0.83) for case–control studies and 0.70 (95% CI: 0.63–0.77) for cohort studies. For different regions, the pooled RRs were 0.74 (95% CI: 0.62–0.88) in Europe, 0.71 (95% CI: 0.64–0.79) in United States/Canada, and 0.40 (95% CI: 0.28–0.57) in Japan. By additional subgroup analysis, a stronger inverse association was shown in caffeinated coffee drinkers (RR 0.66, 95% CI: 0.52–0.83), individuals with the higher body mass index (BMI) (RR 0.65, 95% CI: 0.54–0.79), never smokers (RR 0.68, 95% CI: 0.56–0.84), ever smokers (RR 0.56, 95% CI: 0.45–0.70), and those who never used hormone replacement therapy (HRT) (RR 0.88, 95% CI: 0.79–0.98). The consumption of filtered or boiled coffee showed no significant association. Conclusions Increased coffee intake is associated with a reduced risk of EC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".