Off-Treatment Hepatitis B Virus (HBV) DNA Levels and the Prediction of Relapse After Discontinuation of Nucleos(t)ide Analogue Therapy in Patients With Chronic Hepatitis B: A Prospective Stop Study
Bibliographic record
Abstract
Background: The optimal management remains unknown after nucleos(t)ide analogue (NA) discontinuation in patients with chronic hepatitis B (CHB). This prospective study investigated the role of off-treatment viral kinetics in predicting relapse after discontinuation of NA therapy. Methods: A total of 82 noncirrhotic Asian patients with CHB who discontinued NA therapy according to international guidelines were prospectively followed. Patients with a hepatitis B virus (HBV) DNA level of >2000 IU/mL and an alanine aminotransferase (ALT) level of >2 times the upper limit of normal (clinical relapse) were retreated. Results: Sixty patients were HBV envelope antigen (HBeAg) positive at the start of treatment, and 22 were HBeAg negative. Clinical relapse developed in 28 patients (2-year rates, 31% among HBeAg-positive patients and 53% among HBeAg-negative patients). Age of ≤35 years (hazard ratio [HR], 0.37; P = .026) and end-of-treatment HBsAg level of ≤200 IU/mL (HR, 0.39; P = .078) were independently associated with lower relapse rates. A high risk of biochemical relapse (defined as an ALT level of >2 times the upper limit of normal) was observed if the HBV DNA level was >200000 IU/mL when the level was initially elevated, compared with HBV DNA levels of >2000 to ≤200000 IU/mL (HR, 8.42; P < .001). The risk of biochemical relapse was also high in patients with persistent elevation in the HBV DNA level (confirmed to be >2000 IU/mL within 3 months), compared with the group with transient elevation (HR, 6.87; P < .001). Conclusions: After NA discontinuation, a lower relapse rate was observed in younger patients and in those with low end-of-treatment HBsAg levels. The level and persistence of off-treatment elevated HBV DNA levels were useful in the prediction of a subsequent biochemical relapse and may thus be used to guide off-treatment management.
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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 | 0.001 |
| 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".