Dietary patterns and hepatocellular carcinoma risk: a systematic review and meta-analysis of cohort and case–control studies
Bibliographic record
Abstract
BACKGROUND: Globally, HCC presents a significant health burden, characterized by high incidence and mortality rates. Epidemiological studies have increasingly suggested a link between dietary patterns and the risk of hepatocellular carcinoma (HCC), yet consensus on this relationship remains elusive. OBJECTIVE: This study aims to synthesize existing literature and provide a comprehensive analysis of the association between dietary patterns and HCC risk through meta-analytical methods. METHODS: A systematic search of PubMed, Embase, and the Cochrane Library databases was conducted to identify studies examining common dietary patterns in relation to HCC, published up to August 2023. Study quality was rigorously evaluated using the Newcastle-Ottawa Scale. We employed a random effects model to synthesize effect sizes, calculating hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: We identified 13 papers, of these 10 investigating a priori dietary patterns(index-based dietary patterns) and 3 focusing on a posterior dietary patterns (data-driven dietary patterns). Analysis of a priori dietary patterns revealed that higher scores in the Healthy Eating Index (HEI) & alternative HEI (HR = 0.67, 95% CI: 0.54-0.85), Dietary Approaches to Stop Hypertension (DASH) (HR = 0.77, 95% CI: 0.66-0.91), and the Mediterranean diet (HR = 0.65, 95% CI: 0.56-0.75) were associated with a reduced risk of HCC. Conversely, pro-inflammatory dietary patterns were linked with an increased risk (HR = 2.21, 95% CI: 1.58-3.09). In a posterior dietary patterns, a vegetable-based diet was negatively correlated with HCC risk (HR = 0.63, 95% CI: 0.49-0.81). CONCLUSION: This meta-analysis underscores a significant association between dietary patterns and the risk of HCC. Adherence to healthy dietary patterns characterized by high in vegetables, whole grains, legumes, nuts, and low in red and processed meats may confer a protective effect against HCC, whereas inflammatory diets appear to elevate risk.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.016 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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".