Favourable SVR12 rates with boceprevir or telaprevir triple therapy in HIV/HCV coinfected patients.
Bibliographic record
Abstract
BACKGROUND: Recent publications have reported superior efficacy of telaprevir- or boceprevir-based triple therapy over conventional peginterferon-alfa/ribavirin therapy, albeit with varying rates of adverse events and treatment discontinuations in HIV/HCV coinfected patients. Therefore, the aim of this study is to describe the effectiveness of triple therapy in an HIV/HCV coinfection cohort in the Netherlands. METHODS: HIV-infected patients with chronic HCV genotype 1 starting triple therapy including either boceprevir or telaprevir were enrolled, 26% had F3-F4 fibrosis. Data were assessed at Week 4, 8, 12, 24, 48 and SVR12 (i.e. absence of detectable plasma HCV RNA 12 weeks after completion of treatment). Failure was defined as discontinuation of treatment due to virological failure, adverse events or loss to follow-up. RESULTS: A total of 53 HIV/HCV coinfected patients started peginterferon-alfa/ribavirin therapy with either boceprevir (n = 29) or telaprevir (n = 24). SVR12 was achieved in 19 (66%) of the boceprevir-treated and 15 (63%) of the telaprevir-treated patients. Both prior relapse and achievement of a rapid virological response were associated with a higher SVR12 rate. Non- response, breakthrough and relapse occurred in 4, 1 and 5 patients on boceprevir and 3, 2, 2 on telaprevir, respectively. One patient was lost to follow-up and one patient died due to progression of liver failure. Except for these two patients, no treatment discontinuations were observed due to adverse events. CONCLUSION: In HIV/HCV coinfected patients, boceprevir or telaprevir triple therapy was well tolerated and resulted in favourable SVR12 rates comparable with previous publications concerning HCV mono-infected patients.
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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) | 0.003 | 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".