Lower prevalence of drug resistance mutations at first-line virological failure to first-line therapy with atripla vs. tenofovir + emtricitabine/lamivudine + efavirenz administered on a multiple tablet therapy
Bibliographic record
Abstract
BACKGROUND: Fixed-dose combination antiretroviral therapy administered as a single-tablet regimen (STR) may improve virologic suppression rates. The effect of STRs on development of resistance when virologic failure occurs on STRs is not known. OBJECTIVES: To compare the rate of emergent drug resistance mutations (DRMs) on first-line therapy with coformulated tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC)/efavirenz (EFV) as an STR versus TDF, lamivudine (3TC) or FTC, and EFV given as non-STR. METHODS: Patients from eight cohorts and four randomized clinical trials who received first-line antiretroviral therapy with Atripla (STR group) or with TDF + FTC/3TC + EFV (non-STR group) were eligible if a genotypic resistance test was available immediately after the first episode of viral failure. The DRM list from the 2013 version of IAS-USA was used. RESULTS: One hundred and eighty-six patients were included in the final analysis, 122 (65.6%) from eight cohorts and 64 (34.1%) from four randomized clinical trials. The overall proportion of patients with at least one DRM at viral failure was 67.7%, including 53.4% (31 of 58) in the STR group vs. 74.2% (95 of 128) in the non-STR group (P = 0.005). Among patients exclusively from cohorts, at least one DRM was detected in 53.4% (31 of 58) in the STR group vs. 78.1% (50 of 64) in the non-STR group (P = 0.004). DRMs for individual drugs were: TDF, 15.5 vs. 16.4% (P = 0.87); 3TC/FTC, 31 vs. 35.2% (P = 0.58); and NNRTI, 51.7 vs. 65.6% (P = 0.07). The proportion of patients with an M184V/I among the 128 patients who received FTC was 32.8 vs. 36.2% among the 58 treated with 3TC (P = 0.65). CONCLUSIONS: Compared to patients receiving the STR-Atripla, those receiving the same components individually in a non-STR regimen have a statistically significantly increased risk of selecting for DRMs associated with their drugs on failure.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".