Adherence to assigned dosing regimen and sustained virological response among chronic hepatitis C genotype 1 patients treated with boceprevir plus peginterferon alfa‐2b/ribavirin
Bibliographic record
Abstract
BACKGROUND: Adherence to therapeutic regimens affects the efficacy of peginterferon alfa (P) and ribavirin (R) therapy in patients with chronic hepatitis C virus genotype 1. AIM: To determine if medication adherence impacts efficacy [sustained virological response (SVR)] with triple therapy that includes boceprevir (BOC) plus P/R. METHODS: Adherence was determined in two Phase 3 clinical studies with BOC: SPRINT-2 (previously untreated patients) and RESPOND-2 (patients who failed previous therapy with P/R). Adherence to the assigned duration of the dosing regimen and adherence to the three times a day (t.d.s.) dosing interval of 7-9 h for BOC were assessed by the recording of data from patients' dosing diaries and by the amount of study drug dispensed and returned. RESULTS: Most patients (63-71%) adhered to ≥80% of their assigned treatment duration and achieved SVR rates of 86-90%. In contrast, patients who adhered to <80% of their assigned treatment duration achieved SVR rates of 8-32% (P < 0.0001), particularly low in patients who failed previous therapy (SVR = 8-15%). Different rates of adherence (<60% to >80%) to the t.d.s. dosing interval (7-9 h) with BOC did not influence the SVR rates (SVR = 60-83%) with the exception of patients who failed previous treatment and adhered to <60% of the t.d.s. dosing interval with BOC (SVR = 48-50%; P = 0.005). CONCLUSIONS: The achievement of an SVR is more dependent on adherence to the assigned duration of treatment than adherence to the t.d.s. dosing interval with boceprevir. Adherence to >60% of t.d.s. dosing with boceprevir is important in patients who failed previous therapy.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| 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".