Risk factors for hepatocellular carcinoma in a cohort infected with hepatitis B or C
Bibliographic record
Abstract
BACKGROUND AND AIM: The incidence of hepatocellular carcinoma (HCC) has increased in Australia in recent decades, a large and growing proportion of which occurs among a population chronically infected with hepatitis B virus (HBV) or hepatitis C virus (HCV). However, risk factors for HCC among these high-risk groups require further characterization. METHODS: We conducted a population-based cohort study using HBV and HCV cases notified to the New South Wales Health Department between 2000 and 2007. These were linked to cause of death data, HIV/AIDS notifications, and hospital records. Proportional hazards regression was used to identify significant risk factors for developing HCC. RESULTS: A total of 242 and 339 HCC cases were linked to HBV (n = 43 892) and HCV (n = 83 817) notifications, respectively. For both HBV and HCV groups, being male and increasing age were significantly associated with risk of HCC. Increasing comorbidity score indicated high risk, while living outside urban areas was associated with lower risk. Hazard ratios for males were two to three times those of females. For both HBV and HCV groups, cirrhosis, alcoholic liver disease, and the interaction between the two were associated with significantly and considerably elevated risk. CONCLUSION: This large population-based study confirms known risk factors for HCC. The association with older age highlights the potential impact of HBV and HCV screening of at-risk groups and early clinical assessment. Additional research is required to evaluate the impact of improving antiviral therapy on HCC 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".