Prevalence of hepatitis B antiviral drug resistance variants in North American patients with chronic hepatitis B not receiving antiviral treatment
Bibliographic record
Abstract
Antiviral drug resistance hepatitis B virus (HBV) variants (HBV-DR) occur spontaneously in chronic hepatitis B (CHB) patients and after exposure to nucleos(t)ide analogues (NUCs). We determined the prevalence of HBV-DR variants among participants of the Hepatitis B Research Network (HBRN) Cohort Study conducted at 21 sites in the United States (US) and Canada. Samples obtained from 1342 CHB participants aged ≥18 years, and who were currently not receiving NUCs, were tested for HBV-DR variants by Sanger sequencing. In addition, next generation sequencing (NGS) was used to characterize HBV-DR variants from 66 participants with and 66 participants with no prior NUC exposure matched for HBV genotype and HBV DNA level. Half the participants were men, 75% Asian, 26% HBeAg positive. Primary HBV-DR variants were detected by Sanger sequencing in 16 (1.2%) participants: 2/142 (1.4%) with and 14/1200 (1.2%) without prior NUC exposure; only 1 of these 16 had a secondary variant. In total, 23 (1.7%) participants had secondary variants, including 1 with prior NUC experience. In the subset of 132 participants, NGS detected HBV-DR variants in a higher proportion of participants: primary variants in 18 (13.6%) (8 [12.1%] with, and 10 [15.2%] without prior NUC therapy) and secondary variants in 10 (7.6%) participants. Based on Sanger sequencing, prevalence of primary HBV-DR variants is low (1.2%) among adults with CHB in US/Canada. The similar low prevalence of HBV-DR variants in participants with and without NUC treatment suggests transmission of these variants is uncommon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".