Emergence of Drug Resistance in HIV Type 1–Infected Patients after Receipt of First‐Line Highly Active Antiretroviral Therapy: A Systematic Review of Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Resistance to antiretroviral combination therapy is associated with increased mortality. Understanding the relative risks of emerging resistance to first-line therapy is of importance for both resource-rich and resource-poor settings. METHODS: We undertook an overview of clinical trials of adults receiving first-line highly active antiretroviral therapy (HAART), which consisted of dual nucleoside reverse-transcriptase inhibitors (NRTIs) combined with a third agent (either a nonnucleoside reverse-transcriptase inhibitor [NNRTI] or a ritonavir-boosted protease inhibitor [bPI]). The primary outcome measures were incidences of mutations conferring resistance to key drugs (NRTIs, NNRTIs, or bPIs) per trial at week 48. For meta-analysis, inverse-variance weighting was used to create estimates of overall incidences per group, with exact 95% confidence intervals (95% CIs). RESULTS: The study included 20 clinical trials that comprised 30 treatment arms and 7970 patients. Virologic failure at 48 weeks occurred in 4.9% (95% CI, 3.9%-6.1%) of NNRTI recipients, compared with 5.3% (95% CI, 4.4%-6.4%; P= .50) of bPI recipients. Of failures that were successfully genotyped, the M184V mutation in the HIV reverse transcriptase (lamivudine resistance) occurred in 35.3% (95% CI, 29.3%-41.6%) of patients who started NNRTI-based HAART, compared with 21.0% (95% CI, 14.4%-28.8%; P< .001) for those who received a bPI. For the K65R mutation in the HIV reverse transcriptase (multinucleoside resistance), incidences were 5.3% (95% CI, 2.4%-9.9%) and 0.0% (95% CI, 0.0%-3.6%; P= .01), respectively, in patients treated with non-zidovudine-containing regimens. Resistance to the third agent (an NNRTI or PI) occurred in 53% (95% CI, 46%-60%) and 0.9% (95% CI, 0.0%-6.2%; P< .001) of such patients, respectively. CONCLUSIONS: Initial therapy with bPI-based regimens resulted in less resistance within and across drug classes. This finding is of particular significance for the developing world, where rates of resistance to NRTIs and NNRTIs at 48 weeks are much higher than has been seen in both cohorts and clinical trials in well-resourced countries.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".