Pharmacogenetics of Long‐Term Responses to Antiretroviral Regimens Containing Efavirenz and/or Nelfinavir: An Adult AIDS Clinical Trials Group Study
Bibliographic record
Abstract
BACKGROUND: Efavirenz and nelfinavir are metabolized by cytochrome P-450 (CYP) 2B6 and CYP2C19, respectively, with some involvement by CYP3A. Nelfinavir is a substrate for P-glycoprotein, which is encoded by MDR1. The present study examined associations between genetic variants and long-term responses to treatment. METHODS: Adult AIDS Clinical Trials Group study 384 randomized antiretroviral-naive subjects to receive efavirenz and/or nelfinavir plus 2 nucleoside analogues, with follow-up lasting up to 3 years. Population pharmacokinetics were estimated from a nonlinear mixed-effects model. Polymorphisms in CYP2B6, CYP2C19, CYP3A4, CYP3A5, and MDR1 were characterized. RESULTS: The 504 participants in the genetic study included 340 efavirenz recipients and 348 nelfinavir recipients (184 of the 504 participants received both efavirenz and nelfinavir). Of the participants, 49% were white, 31% were black, and 19% were Hispanic. Plasma exposure to efavirenz and nelfinavir in each population was significantly associated with the polymorphisms CYP2B6 516G-->T and CYP2C19 681G-->A, respectively. Among efavirenz recipients, the MDR1 position 3435 TT genotype was associated with decreased likelihood of virologic failure and decreased emergence of efavirenz-resistant virus but not with plasma efavirenz exposure. Among nelfinavir recipients, a trend toward decreased virologic failure was associated with the polymorphism CYP2C19 681G-->A. CONCLUSIONS: Genetic variants predict plasma exposure to efavirenz and nelfinavir, and they may predict virologic failure and/or emergence of drug-resistant virus. These associations with treatment responses must be validated in other studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".