Evolution of Protease Inhibitor Resistance in Human Immunodeficiency Virus Type 1 Infected Patients Failing Protease Inhibitor Monotherapy as Second-line Therapy in Low-income Countries: An Observational Analysis Within the EARNEST Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Limited viral load (VL) testing in human immunodeficiency virus (HIV) treatment programs in low-income countries often delays detection of treatment failure. The impact of remaining on failing protease inhibitor (PI)-containing regimens is unclear. METHODS: We retrospectively tested VL in 2164 stored plasma samples from 386 patients randomized to receive lopinavir monotherapy (after initial raltegravir induction) in the Europe-Africa Research Network for Evaluation of Second-line Therapy (EARNEST) trial. Protease genotypic resistance testing was performed when VL >1000 copies/mL. We assessed evolution of PI resistance mutations from virological failure (confirmed VL >1000 copies/mL) until PI monotherapy discontinuation and examined associations using mixed-effects models. RESULTS: Median post-failure follow-up (in 118 patients) was 68 (interquartile range, 48-88) weeks. At failure, 20% had intermediate/high-level resistance to lopinavir. At 40-48 weeks post-failure, 68% and 51% had intermediate/high-level resistance to lopinavir and atazanavir; 17% had intermediate-level resistance (none high) to darunavir. Common PI mutations were M46I, I54V, and V82A. On average, 1.7 (95% confidence interval 1.5-2.0) PI mutations developed per year; increasing after the first mutation; decreasing with subsequent mutations (P < .0001). VL changes were modest, mainly driven by nonadherence (P = .006) and PI mutation development (P = .0002); I47A was associated with a larger increase in VL than other mutations (P = .05). CONCLUSIONS: Most patients develop intermediate/high-level lopinavir resistance within 1 year of ongoing viral replication on monotherapy but retain susceptibility to darunavir. Viral load increased slowly after failure, driven by non-adherence and PI mutation development. CLINICAL TRIALS REGISTRATION: NCT00988039.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".