Comparative Efficacy of Lamivudine and Emtricitabine: A Systematic Review and Meta-Analysis of Randomized Trials
Bibliographic record
Abstract
INTRODUCTION: Lamivudine and emtricitabine are considered equivalent by several guidelines, but evidence of comparable efficacy is conflicting. METHODS: We searched two databases up to June 30 2013 to identify randomized and quasi-randomized trials in which lamivudine and emtricitabine were used as part of combination antiretroviral therapy for treatment-naïve or experienced HIV-positive adult patients. We only included trials where partner drugs in the regimen were identical or could be considered to be comparable. We allowed for comparisons between tenofovir and abacavir provided the study population did not begin treatment with a viral load >100,000 copies/ml. RESULTS: 12 trials contributed 15 different randomized comparisons providing data on 2251 patients receiving lamivudine and 2662 patients receiving emtricitabine. Treatment success was not significantly different in any of the 12 trials. In the three trials that directly compared lamivudine and emtricitabine, the relative risk for achieving treatment success was non-significant (RR 1.03 95%CI 0.96-1.10). For all trials combined, the pooled relative risk for treatment success was not significantly different (RR 1.00, 95%CI 0.97-1.02). No heterogeneity was observed (I (2) = 0). Similarly, there was no difference in the pooled relative risk for treatment failure (RR 1.08, 95%CI 0.94-1.22, I (2) = 3.4%). CONCLUSIONS: The findings of this systematic review suggest that lamivudine and emtricitabine are clinically equivalent.
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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 | 0.032 | 0.070 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.027 | 0.035 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".