Fiber and whole grain intakes in relation to liver cancer risk: An analysis in 2 prospective cohorts and systematic review and meta-analysis of prospective studies
Bibliographic record
Abstract
BACKGROUND AND AIMS: The association between fiber or whole grain intakes and the risk of liver cancer remains unclear. We assessed the associations between fiber or whole grain intakes and liver cancer risk among 2 prospective studies, and systematically reviewed and meta-analyzed these results with published prospective studies. APPROACH AND RESULTS: A total of 111,396 participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and 26,085 men from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study were included. Intakes of total fiber and whole grains were estimated from validated food frequency questionnaires. Study-specific HRs and 95% CI with liver cancer risk were estimated using multivariable-adjusted Cox regression. We systematically reviewed existing literature, and studies were combined in a dose-response meta-analysis. A total of 277 (median follow-up = 15.6 y) and 165 (median follow-up = 16.0 y) cases of liver cancer were observed in Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, respectively. Dietary fiber was inversely associated with liver cancer risk in Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (HR 10g/day : 0.69; 95% CI: 0.55-0.86). No significant associations were observed between whole grain intakes and liver cancer risk in either study. Our meta-analysis included 2383 incident liver cancer cases (7 prospective cohorts) for fiber intake and 1523 cases (5 prospective cohorts) for whole grain intake; combined HRs for liver cancer risk were 0.83 (0.76-0.91) per 10 g/day of fiber and 0.92 (0.85-0.99) per 16 g/day (1 serving) of whole grains. CONCLUSIONS: Dietary fiber and whole grains were inversely associated with liver cancer risk. Further research exploring potential mechanisms and different fiber types is needed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.000 | 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".