Relationship between hepatitis B core‐related antigen levels and sustained <scp>HB</scp>eAg seroconversion in patients treated with nucleo(s)tide analogues
Bibliographic record
Abstract
Hepatitis B e antigen (HBeAg) seroconversion experienced during nucleo(s)tide analogue (NUC) therapy is often not sustained. We aimed to study whether hepatitis B core-related antigen (HBcrAg) levels predict sustained HBeAg seroconversion in patients treated with NUCs. We studied HBeAg-positive patients treated with NUCs for at least 6 months. We quantified HBcrAg at baseline and at the time of HBeAg seroconversion and studied the relationship with HBeAg seroconversion and subsequent relapse. HBcrAg was quantified at baseline in 196 patients; levels varied significantly by HBV genotype and correlated with HBsAg, HBV DNA and HBeAg. Baseline HBcrAg levels were lower in patients who achieved HBeAg seroconversion than in those who did not; the unadjusted hazard ratio (HR) was 0.802 (95% CI: 0.656-0.980, P = 0.031); and this association was not sustained in multivariate analysis. HBcrAg remained detectable in all patients at the time of HBeAg seroconversion. Higher HBcrAg at the time of seroconversion was an independent predictor of relapse (adjusted HR: 1.855 (95% CI: 1.099-3.133, P = 0.021), and none of the patients with HBcrAg < 4.90 log U/mL experienced relapse. Baseline HBcrAg is not an independent predictor of HBeAg seroconversion during NUC therapy. HBcrAg remains detectable in patients after HBeAg seroconversion. Patients with lower levels at the time of seroconversion have a higher probability of sustained HBeAg seroconversion.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".