Risk factors of hepatocellular carcinoma associated with nonalcoholic fatty liver disease: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is currently an important chronic liver disease threatening human life and health. OBJECTIVE: To investigate the risk factors of hepatocellular carcinoma (HCC) associated with nonalcoholic fatty liver disease (NAFLD) by systematic review. METHODS: We conducted a systematic review and meta-analysis. A systematic search of Chinese and English databases (PubMed, Web of Science, Cochrane Library, China national knowledge infrastructure (CNKI), Wanfang database, and VIP database) was performed until June 30, 2023. Studies were included to investigate the risk factors for HCC in patients with NAFLD. Quality evaluation was performed using the Newcastle-Ottawa Literature Quality Evaluation Scale, and then hazard ratios (HRs) for different influencing factors were combined. RESULTS: We reviewed the results of 12 high-quality cohort studies involving 738,934 patients with NAFLD and 1,480 developed HCC. A meta-analysis based on a random-effects model showed that advanced age (HR = 1.81, 95% CI: 1.51-2.17), male gender (HR = 2.51, 95% CI: 1.67-3.78), hypertension (HR = 1.87, 95% CI: 1.05-3.33), and diabetes (HR = 2.27, 95% CI: 1.63-3.16) were risk factors for HCC in NAFLD, and the differences were statistically significant. However, there was no statistically significant effect of current smoking (HR = 1.45, 95% CI: 0.72-2.92) and dyslipidemia (HR = 1.03, 95% CI: 0.72-1.47) on HCC incidence in this study. CONCLUSION: Age, sex, hypertension and diabetes are risk factors for HCC in NAFLD patients. Diabetic NAFLD patients have a 2.27-fold increased risk of HCC, and health education and intervention for elderly, male, NAFLD patients with diabetes and hypertension need to be strengthened to promote a reduction in the risk of HCC.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.033 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".