Highly frequent HIV-1 minority resistant variants at baseline of the ANRS 139 TRIO trial had a limited impact on virological response
Bibliographic record
Abstract
OBJECTIVES: To assess the prevalence of minority resistant variants (MRVs) at baseline and their impact on the virological response. The ANRS 139 TRIO trial evaluated the combination of raltegravir, etravirine and darunavir, plus an optimized background therapy, in 87% of cases. Patients were highly experienced and harboured multiresistant viruses, but were naive to the three drugs, and showed a high level of virological suppression. METHODS: Ultra-deep sequencing of reverse transcriptase, protease and integrase regions was performed at the trial baseline, and sequences were interpreted according to the ANRS algorithm. MRVs were assessed using MiSeq and 454 technologies (limit of detection 1%). RESULTS: At baseline, minority variants with at least one NRTI, one NNRTI, one PI, one major PI or an integrase inhibitor resistance-associated mutation were present in 46%, 45%, 68%, 24% and 13% of patients, respectively. When minority variants are taken into account, the prevalence of resistance to etravirine, darunavir and raltegravir at baseline was 29%, 40% and 9%, respectively. No difference was observed in the prevalence of MRVs between patients with virological failure and those with virological success, except a trend for patients exhibiting baseline etravirine MRVs (50% versus 26%, P = 0.09). CONCLUSIONS: We have shown a high level of MRVs at baseline in highly pre-treated patients harbouring multiresistant viruses. However, these MRVs were not associated with an increased risk of virological failure, except for a trend for etravirine MRVs.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".