Differential Relapse Patterns After Discontinuation of Entecavir vs Tenofovir Disoproxil Fumarate in Chronic Hepatitis B
Bibliographic record
Abstract
BACKGROUND AND AIMS: Whether entecavir (ETV) and tenofovir disoproxil fumarate (TDF) differentially affect relapse and outcomes following treatment discontinuation across different patient subpopulations remains unclear. We aimed to compare rates of off-therapy hepatitis B surface antigen (HBsAg) loss, virological and clinical relapse, and retreatment between chronic hepatitis B (CHB) patients who discontinued TDF or ETV therapy. METHODS: This study included 1402 virally suppressed CHB patients who stopped either ETV (n = 981) or TDF (n = 421) therapy between 2001 and 2020 from 13 participating centers across North America, Europe, and Asia. All patients were hepatitis B e antigen-negative at treatment discontinuation. Inverse probability of treatment weighting was used to balance the treatment groups. Outcomes were analyzed using survival methods. RESULTS: During a median off-treatment follow-up of 18 months, HBsAg loss occurred in 96 (6.8%) patients overall. Compared with ETV, TDF was associated with a higher rate of HBsAg loss (P = .03); however, the association was no longer significant after statistical adjustment (P = .61). Virological relapse occurred earlier among TDF-treated patients (P < .01); nonetheless, rates became comparable after the first year off therapy (P = .49). TDF was significantly associated with a higher clinical relapse rate than ETV throughout follow-up (P < .01). The development of a virological or clinical relapse did not affect the rate of HBsAg loss. Retreatment rates were not significantly different between the treatment groups. CONCLUSIONS: TDF and ETV have differential relapse patterns but are associated with similar rates of HBsAg loss and retreatment following discontinuation. Finite therapy can be considered for CHB patients on either TDF or ETV therapy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".