Lamivudine Monotherapy-Based cART Is Efficacious for HBV Treatment in HIV/HBV Coinfection When Baseline HBV DNA <20,000 IU/mL
Bibliographic record
Abstract
BACKGROUND: Although combination antiretroviral therapy (cART) including tenofovir (TDF)+lamivudine (3TC) or emtricitabine (FTC) is recommended for treatment of HIV/HBV coinfected patients, TDF is unavailable in some resource-limited areas. Some data suggest that 3TC monotherapy-based cART may be effective in patients with low pretreatment HBV DNA. METHODS: Prospective study of 151 Chinese HIV/HBV coinfected subjects of whom 60 received 3TC-based cART and 91 received TDF+3TC-based cART. Factors associated with HBV DNA suppression at 24 and 48 weeks, including anti-HBV drugs, baseline HBV DNA, and baseline CD4 cell count, were evaluated overall and stratified by baseline HBV DNA using Poisson regression with a robust error variance. RESULTS: Baseline HBV DNA ≥20,000 IU/mL was present in 48.3% and 44.0% of subjects in the 3TC and TDF groups, respectively (P = 0.60). After 48 weeks of treatment, HBV DNA suppression rates were similar between these 2 groups (96.8% vs. 98.0% for 3TC and TDF+3TC, P > 0.999) in subjects with baseline HBV DNA <20,000 IU/mL; whereas in those with baseline HBV DNA ≥20,000 IU/mL, TDF+3TC was associated with higher suppression rates (34.5% vs. 72.5% in 3TC and TDF+3TC groups, respectively, P = 0.002). In stratified multivariate regression, TDF use (RR 1.98, P = 0.010) and baseline HBV DNA (per 1 log increase in International Units Per Milliliter, RR 0.74, P < 0.001) were associated with HBV DNA suppression only when baseline HBV DNA ≥20,000 IU/mL. CONCLUSION: This study suggests that 3TC monotherapy-based cART is efficacious for HBV treatment through 48 weeks in HIV/HBV coinfection when baseline HBV DNA <20,000 IU/mL. Studies with long-term follow-up are warranted to determine if this finding persists.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".