Adherence to pan‐genotypic glecaprevir/pibrentasvir and efficacy in HCV‐infected patients: A pooled analysis of clinical trials
Bibliographic record
Abstract
BACKGROUND & AIMS: Adequate adherence to hepatitis C virus (HCV) treatment is believed to be a key component of treatment success because non-adherence can potentially result in treatment failure and the emergence of resistant viral variants. This analysis assessed factors associated with non-adherence to glecaprevir/pibrentasvir (G/P) therapy and the impact of non-adherence on sustained virological response at post-treatment week 12 (SVR12) rates in HCV genotype (GT) 1-6-infected patients. METHODS: Adherence was calculated by pill counts at study visits during treatment, and defined as having a lowest treatment adherence of ≥80% and ≤120% at each study visit. Exploratory logistic regression modelling assessed predictors of non-adherence to G/P therapy. SVR12 rates by treatment adherence were assessed in the intent-to-treat (ITT) population and modified ITT (mITT) population, which excludes non-virological failures. RESULTS: Overall, 97% (2024/2091) of patients were adherent to G/P therapy at all consecutive study visits. Alcohol use was the only baseline characteristic independently associated with non-adherence to G/P therapy (OR: 2.38; 95% CI: 1.13-5.01; P = .022). In the mITT population, overall SVR12 rates were high both in patients who were adherent to G/P therapy and those who were not (99% [1983/2008] and 95% [58/61] respectively; P = .047). Corresponding SVR12 rates in the ITT population were 98% (1983/2024) and 87% (58/67) respectively. CONCLUSIONS: Most patients adhered to G/P therapy. SVR12 rates were high both in patients who were adherent to G/P treatment and those who were not. Patient education on treatment adherence should remain an important part of HCV treatment. CLINICAL TRIALS REGISTRATION: NCT02604017, NCT02640482, NCT02640157, NCT02636595, NCT02642432, NCT02651194, NCT02243293, NCT02446717.
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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 | 0.031 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".