Coffee Consumption and Risk of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma by Sex: The Liver Cancer Pooling Project
Bibliographic record
Abstract
BACKGROUND: Coffee consumption has been reported to be inversely associated with hepatocellular carcinoma (HCC), the most common type of liver cancer. Caffeine has chemopreventive properties, but whether caffeine is responsible for the coffee-HCC association is not well studied. In addition, few studies have examined the relationship by sex, and no studies have examined whether there is an association between coffee and intrahepatic cholangiocarcinoma (ICC), the second most common type of liver cancer. METHODS: In the Liver Cancer Pooling Project, a consortium of U.S.-based cohort studies, data from 1,212,893 individuals (HCC, n = 860; ICC, n = 260) in nine cohorts were pooled. Multivariable-adjusted hazard ratios (HR) and 95% confidence intervals (CI) were estimated using proportional hazards regression. RESULTS: Higher coffee consumption was associated with lower risk of HCC (HR>3 cups/day vs. non-drinker, 0.73; 95% CI, 0.53-0.99; Ptrend cups/day = <0.0001). More notable reduced risk was seen among women than men (Pinteraction = 0.07). Women who consumed more than three cups of coffee per day were at a 54% lower risk of HCC (HR, 0.46; 95% CI, 0.26-0.81), whereas men had more modest reduced risk of HCC (HR, 0.93; 95% CI, 0.63-1.37). The associations were stronger for caffeinated coffee (HR>3 cups/day vs. non-drinker, 0.71; 95% CI, 0.50-1.01) than decaffeinated coffee (HR, 0.92; 95% CI, 0.55-1.54). There was no association between coffee consumption and ICC. CONCLUSIONS: These findings suggest that, in a U.S. population, coffee consumption is associated with reduced risk of HCC. IMPACT: Further research into specific coffee compounds and mechanisms that may account for these associations is needed.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".