Incidence of Hepatocellular Carcinoma and Decompensated Liver Cirrhosis and Prognostic Accuracy of the PAGE-B HCC Risk Score in a Low Endemic Hepatitis B Virus Infected Population
Bibliographic record
Abstract
Purpose: We aimed to determine incidence of hepatocellular carcinoma (HCC) and decompensated liver cirrhosis in persons with chronic hepatitis B virus (HBV) infection in Denmark stratified by disease phase, liver cirrhosis, and treatment status at baseline. Additionally, we aimed to assess the prognostic value of the PAGE-B HCC risk score in a mainly non-cirrhotic population. Patients and Methods: In this register-based cohort study, we included all individuals over the age of 18, with chronic HBV infection first registered between 2002 and 2016 in at least one of three nationwide registers. The study population was followed until HCC, decompensated liver cirrhosis, death, emigration, or December 31, 2017, which ever came first. Results: Among 6016 individuals included in the study, 10 individuals with and 23 without baseline liver cirrhosis developed HCC during a median follow up of 7.3 years (range 0.0-15.5). This corresponded to five-year cumulative incidences of 7.1% (95% confidence interval (CI) 2.0-12.3) and 0.2% (95% CI 0.1-0.4) in persons with and without baseline liver cirrhosis. The five-year cumulative incidence of decompensated liver cirrhosis was 0.7% (95% CI 0.5-1.0). Among 2038 evaluated for liver events stratified by disease phase, incidence of HCC was low in all who were non-cirrhotic and untreated for HBV at baseline. PAGE-B score was evaluated in 1529 persons. The 5-year cumulative incidence of HCC was 0, 0.8 (95% CI 0.5-1.8), and 8.7 (95% CI 1.0-16.4) in persons scoring <10, 10-17 and >17, respectively (c-statistic 0.91 (95% CI 0.84-0.98)). Conclusion: We found low incidence of HCC and decompensated liver cirrhosis in persons with chronic HBV infection in Denmark. Moreover, the PAGE-B score showed good accuracy for five-year risk of developing HCC in the population with chronic HBV infection in Denmark.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".