Epidemiology, Treatment Patterns and Survival in Canadian Patients With Chronic Hepatitis B‐Related Hepatocellular Carcinoma
Bibliographic record
Abstract
Chronic hepatitis B (CHB) is the leading cause of hepatocellular carcinoma (HCC) globally. We described and evaluated the outcomes of patients with CHB-HCC in Canada. In this retrospective cross-sectional cohort study, data were analysed from CHB mono-infected subjects seen between 1 January 2012 and 31 December 2022, and entered the Canadian Hepatitis B Network Registry. Descriptive analysis and chi-squared modelling were used to compare cohorts, followed by multivariable survival analysis regarding survival post-diagnosis. Statistical analyses were completed in R version 2.2. Of the 6711 patients with CHB who met inclusion criteria, 232 (3.5%) developed HCC. Compared with the CHB cohort, the majority of CHB-HCC cohort were male, SEA and HBeAg negative and born in endemic area (80% vs. 56%, 73% vs. 55%, 84% vs. 54%, 64% vs. 40% and all p < 0001). Overall, median HBV DNA level was log 2.54 (IQR: 0-4.04). Advanced liver disease, defined as minimum Fibrosis stage F3, was seen in 9.4% of overall cohort, but 92% of HCC cohort. At diagnosis, median tumour size was 2.5 cm (IQR: 1.7-4.0) and mean tumour number was 1.33 (SD: 1.33), with 81% of patients BCLC 0-A. Fifty-three per cent of patients were diagnosed with HCC as part of surveillance protocols. The survival rate after HCC diagnosis was 78.7%, during the median follow-up of 52.9 months (IQR: 17-90). In multivariable analysis, survival was significantly correlated with diagnosis through the screening programme. In this large cohort of patients with CHB-HCC, the majority of patients were detected with early-stage HCC and received treatment with curative intent, resulting in strong survival rates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".