Review article: long‐term safety of nucleoside and nucleotide analogues in <scp>HBV</scp>‐monoinfected patients
Bibliographic record
Abstract
BACKGROUND: Nucleos(t)ide analogues (NUCs) for chronic hepatitis B treatment achieve high rates of viral suppression and are generally well tolerated. Entecavir (ETV) and tenofovir disoproxil fumarate (TDF) are the currently preferred first-line agents. The safety of these agents in clinical practice is particularly relevant since long-term treatment is usually required. AIM: To summarise and critically discuss recent real-world evidence on the safety of treatment with ETV or TDF in hepatitis B virus (HBV)-monoinfected patients. METHODS: PubMed and conference proceedings up to 15th June 2015 were searched using the terms ((((Hepatitis_B) OR HBV) AND ((tenofovir) OR entecavir)) AND (((lactic_acidosis) OR bone) OR renal)). RESULTS: In selected populations included in registration studies, both ETV and TDF were well tolerated with no clinically significant renal toxicity or lactic acidosis. Growing 'real-world' clinical experience with these agents includes some reports of ETV-associated lactic acidosis and TDF-associated renal impairment; however, evidence from cohort studies appears to be conflicting. In the case of ETV-related lactic acidosis, a small number of cases have been reported, all in patients with decompensated cirrhosis. The degree of association between TDF treatment and changes in markers of renal function varies between studies: discrepancies may result from the use of different definitions and cut-offs for reporting renal toxicities, and differences in patient populations. CONCLUSIONS: Pre-treatment and on-treatment monitoring of eGFR and phosphorus, with prompt appropriate dose adjustment or treatment switch can minimise the impact of NUC renal toxicity. Standardisation of measures of renal impairment and identification of early molecular markers remain an unmet need.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".