Association of Baseline Hepatitis B Virus DNA and On-Treatment Risk of Cirrhosis and Hepatocellular Carcinoma
Bibliographic record
Abstract
Background: Recent studies suggest an inverse relationship between baseline levels of hepatitis B virus (HBV) DNA and on-treatment risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB). However, data are limited to Asian cohorts, and it is unclear if similar associations hold true for non-Asians with CHB. We aimed to evaluate association of baseline HBV DNA with long-term risks of cirrhosis and HCC among a predominantly non-Asian cohort of CHB patients in the USA. Methods: Using longitudinal data from the national Veterans Affairs database, we evaluated the risk of cirrhosis or HCC among adults with non-cirrhotic CHB who are on continuous antiviral therapy, stratified by moderate levels of baseline HBV DNA (4.00 - 6.99 log 10 IU/mL) vs. high levels of baseline HBV DNA (7.00 log 10 IU/mL or higher). Propensity score weighting was applied, and competing risks cumulative incidence functions and Cox proportional hazards models were utilized. Results: Among 1,129 non-cirrhotic CHB patients (41% non-Hispanic White, 36% African American, mean age 57.0 years, 62.2% hepatitis B e antigen (HBeAg) positive), 585 had moderate levels of baseline HBV DNA and 544 had high HBV DNA. After propensity score weighting, no significant difference in risk of cirrhosis was observed between moderate vs. high baseline HBV DNA (4.55 vs. 5.22 per 100 person-years, hazard ratio (HR): 0.87, 95% confidence interval (CI): 0.69 - 1.09, P = 0.22), but risk of HCC was significantly higher in patients with moderate vs. high baseline HBV DNA (0.84 vs. 0.69 per 100 person-years, HR: 1.33, 95% CI: 1.09 - 1.62, P < 0.01). Conclusions: Among a national cohort of predominantly non-Asian US veterans with non-cirrhotic CHB on antiviral therapy, moderate levels of baseline HBV DNA was associated with higher risk of HCC than high HBV DNA. Gastroenterol Res. 2024;17(3):109-115 doi: https://doi.org/10.14740/gr1735
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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 | 0.000 | 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) | 0.003 | 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".