Discontinuation of Enfuvirtide in Heavily Pretreated HIV-Infected Individuals
Bibliographic record
Abstract
BACKGROUND: Enfuvirtide was shown to be highly effective in treatment- experienced patients. Data on discontinuation of enfuvirtide and switch to new antiretroviral drugs are scarce. We aimed to evaluate the efficacy and the impact of discontinuing and/or switching enfuvirtide on virologic and clinical parameters in clinical practice. METHODS: All HIV-infected individuals participating in the Swiss HIV Cohort Study who were treated with enfuvirtide for at least 4 weeks in combination with an optimized background antiretroviral regimen were included in this study. RESULTS: A total of 151 patients were analyzed. The median baseline CD4 cell count was 108 cells/microL (interquartile range [IQR] 50-206) and HIV RNA was 4.7 log10 copies/mL (IQR 4.1-5.2). Virologic suppression, defined as a viral load below 50 copies/mL at 12 months, was achieved by 57.6% of patients. Overall, a median CD4 cell increase of 121 cells/microL (IQR 50-189) from baseline was noted. Up to 50% of patients discontinued enfuvirtide within the first year of treatment, mainly because of the patient's choice. After discontinuation of enfuvirtide, high rates of virologic failure and clinical progression were observed, notably when CD4 cell count at stopping enfuvirtide was below 100 cells/microL and no switch to new potent antiretroviral drugs such as darunavir, maraviroc, or raltegravir was performed. CONCLUSIONS: Enfuvirtide provides high virologic and immunologic response in treatment-experienced patients in the setting of clinical practice. Enfuvirtide should not be discontinued but should be replaced by new potent antiretrovirals, particularly in case of severe immunosuppression.
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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) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".