Prevalence of Rilpivirine and Etravirine Resistance Mutations in HIV-1 Subtype C-Infected Patients Failing Nevirapine or Efavirenz-Based Combination Antiretroviral Therapy in Botswana
Bibliographic record
Abstract
Rilpivirine (RPV) and Etravirine (ETR) are approved second-generation non-nucleoside reverse transcriptase inhibitors (NNRTIs) for HIV treatment. There is a cross-resistance HIV mutation profile between first- and second-generation NNRTI drugs. We determined the prevalence of HIV-1 drug resistance mutations (DRMs) to RPV and ETR in Botswana. A total of 168 HIV-1 polymerase gene sequences from participants failing nevirapine (NVP)- or efavirenz (EFV)-containing regimens were analyzed for DRMs using the Stanford University HIV drug resistance database. Forty-one sequences were from an adult antiretroviral therapy (ART) study, the Tshepo study, and 127 from a prevention of mother-to-child transmission (PMTCT) study, the Mashi study, all conducted in Botswana. Prevalence of RPV and ETR highest DRM in the adult ART study (n = 41) were K101E (26.2%), E138A (23.8%), and Y181C (26.2%). The PMTCT cohort's (n = 127) high prevalence mutations were Y181C (15.7%), E138A (15%), and K101E (11%). A total of 42.9% and 3.2% of patients in the adult ART study and PMTCT study, respectively, had three or more NNRTI mutations at virologic failure. We identified HIV-1 mutations conferring resistance to RPV and ETR even though they have not been used in Botswana. Of concern was the high proportion of sequences from the adult ART study that displayed multiple DRMs; as the number of NNRTI mutations increases, the level of cross-resistance increases. It is plausible that patients displaying such profiles maybe at increased risk of failing second-generation NNRTI drugs, hence, calls for genotyping in patients with prior NVP or efavirenz exposure before prescription of RPV- or ETR-containing cART.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".