Review article: switching patients with chronic hepatitis B to tenofovir alafenamide—a review of current data
Bibliographic record
Abstract
BACKGROUND: The nucleos(t)ide analogues (NAs) entecavir (ETV), tenofovir disoproxil fumarate (TDF) and tenofovir alafenamide (TAF) are preferred treatment options for patients with chronic hepatitis B infection (CHB). However, resistance to ETV has been reported, especially with prior exposure to other NAs, and long-term TDF treatment has been associated with decline in renal function and loss of bone mineral density in some patients. Consequently, TAF may be preferable to ETV, TDF or other NAs in specific circumstances such as in patients with risk of bone or renal complications, elderly patients or those with previous NA experience. AIM: To provide a summary of the available efficacy and safety data following switch to TAF from other NAs in patients with CHB in clinical studies and real-world settings. METHODS: Literature searches were performed on PubMed and abstracts from three major international liver congresses between 2019 and 2021. Studies that included efficacy and/or safety data for patients with CHB switching from any NA to TAF were selected. RESULTS: Thirty-six papers and abstracts were included in this narrative review. Switching from TDF to TAF maintained or improved virological and biochemical responses with improved bone and renal safety. Switching from ETV or other NAs to TAF maintained or improved virological and biochemical responses and varying results for bone and renal safety. CONCLUSIONS: Switching to TAF appears to maintain or improve virological, biochemical and bone- and renal-related safety outcomes. These data support the concept of switching to TAF in some patients with CHB based on their individual circumstances.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".