Sustained virological response after treatment with direct antiviral agents in individuals with HIV and hepatitis C co‐infection
Bibliographic record
Abstract
INTRODUCTION: Randomized trials and observational studies have consistently reported rates of sustained virological response (SVR), equivalent to hepatitis C virus (HCV) cure, as high as 95% following treatment with direct-acting antiviral (DAA) treatment in individuals with HIV and HCV co-infection. However, large studies assessing whether SVR rates differ according to demographic and clinical strata are lacking. Additionally, the SVR rates reported in the literature were typically computed in non-random samples of individuals with available post-DAA HCV-RNA measures. Here, we aimed to estimate the probability of SVR after DAA treatment initiation in persons with HIV and HCV co-infection overall and by demographic and clinical characteristics with and without adjustment for missing HCV-RNA testing. METHODS: We included adults with HIV-HCV co-infection who received DAA treatment between 2014 and 2020 in HepCAUSAL, an international collaboration of cohorts from Europe and North America. We estimated the proportions of DAA recipients who had documented SVR (defined as an undetectable HCV-RNA at least 12 weeks after the end of DAA treatment) overall and by strata defined by age, sex, presence of cirrhosis, calendar period, mode of HIV acquisition, CD4 cell count and HCV genotype at DAA treatment. We then compared these rates with those obtained using the parametric g-formula to impute SVR status for individuals with no SVR assessment. RESULTS AND DISCUSSION: A total of 4527 individuals who initiated DAA treatment (88% males, median [IQR] age 56 [50, 62] years) were included. Of the total of 642 (14%) individuals had no HCV-RNA test on or after 12 weeks after the end of treatment. The overall observed and g-formula imputed SVR rates were 93% (95% CI 93, 94) and 94% (95% CI 92, 95), respectively. SVR estimates were similarly high across all strata. A substantial proportion of individuals who received DAA treatment were never assessed for SVR post-DAA and strategies for more systematic routine HCV-RNA testing should be considered. CONCLUSIONS: Our estimates with and without adjustment for missing HCV-RNA testing indicate SVR rates of approximately 95%, like those reported in clinical trials.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".