Sustained HIV RNA suppression after switching from enfuvirtide to etravirine in the early access programme
Bibliographic record
Abstract
Sir, The next-generation non-nucleoside reverse transcriptase inhibitor (NNRTI) etravirine (formerly known as TMC125) and the fusion inhibitor enfuvirtide have both shown improved efficacy over optimized background treatments in the DUET and TORO trials, respectively.1–3 Due to the cost of enfuvirtide and the need for twice-daily injections, switching from enfuvirtide to etravirine could improve convenience and tolerability, and reduce treatment costs. Two recent pilot studies have shown sustained HIV RNA suppression, 7 months after switching from enfuvirtide to raltegravir in virologically suppressed patients.4,5 A pilot study also showed sustained HIV RNA suppression for 6 months, after switching from enfuvirtide and protease inhibitors (PIs) to etravirine and darunavir/ritonavir, in 10 American patients.6 The TMC125-C214 trial (global etravirine early access programme) recruited triple class experienced patients who had received at least two previous PI-containing regimens. Patients with undetectable HIV RNA levels at the screening visit were permitted to switch from enfuvirtide to etravirine for either intolerance or simplification. The patients were allowed to optimize other parts of the background regimen at the time of switch from enfuvirtide to etravirine. Patients were followed up for HIV RNA, CD4 count and serious adverse events. All patients signed informed consent and the programme was approved by local and national ethics committees. We analysed 24 week data for 22 patients in Europe and 15 patients in Canada. Of these 37 patients, 11% were female and 95% were Caucasian, with a mean age of 48 years (range 36–62). The baseline mean CD4 cell count was 380 cells/mm3 [95% confidence interval (CI): 312–449].
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".