Burden of Nonnucleoside Reverse Transcriptase Inhibitor Resistance in HIV-1-Infected Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The prevalence of HIV drug resistance varies with geographic location, year, and treatment exposure. This study generated yearly estimates of nonnucleoside reverse transcriptase inhibitor (NNRTI) resistance in treatment-naive (TN) and treatment-experienced (TE) patients in the United States (US), Europe (EU), and Canada. Studies reporting NNRTI resistance identified in electronic databases and 11 conferences were analyzed in three groups: (1) TN patients in one of four geographic regions [US, Canada, EU countries with larger surveillance networks ("EU1"), and EU countries with fewer data ("EU2")]; (2) TE patients from any region; and (3) TN patients failing NNRTI-based treatments in clinical trials. Analysis data included 158 unique studies from 22 countries representing 84 cohorts of TN patients, 21 cohorts of TE patients, and 8 trials reporting resistance at failure. From 1995 to 2000, resistance prevalence in TN patients increased in US and EU1 from 3.1% to 7.5% and 0.8% to 3.6%, respectively. Resistance in both regions stabilized in 2006 onward. Little resistance was identified in EU2 before 2000, and increased from 2006 (5.0%) to 2010 (13.7%). One TN Canadian study was identified and reported resistance of 8.1% in 2006. Half of TN clinical trial patients had resistance after treatment failure at weeks 48-144. Resistance in TE patients increased from 1998 (10.1%) to 2001 (44.0%), then decreased after 2004. Trends in NNRTI resistance among TN patients show an increased burden in the US and some EU countries compared to others. These findings signify a need for alternate first-line treatments in some regions.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".