Real-world health care utilization in treatment of HCV: Results from the Canadian SIMPLE observational trial
Bibliographic record
Abstract
Background: As hepatitis C virus (HCV) treatment continues to evolve, there is an ongoing need to understand and optimize real-world disease management. The primary objective of the SIMPLE study was to describe the real-life management of genotype 1 (G1) HCV in Canada treated with boceprevir + pegylated interferon and ribavirin therapy. Methods: This was an observational, prospective cohort, multicentre, non-interventional study of patients with G1 HCV. A single cohort of adult patients were to be managed as per standard of care (SoC) and treated with 4 weeks of PegRBV dual therapy, followed by boceprevir + PegRBV for 24-44 weeks, with 24-weeks follow-up. Treatment compliance, health care resource utilization (HCRU), HCV viral load, and hematological adverse event (AE) data were collected. Results: This study enrolled 159 patients. All investigators were well educated on the Canadian consensus guidelines for HCV management but only a minority of patients were treated according to treatment guidelines. Viral response was achieved by >50% of patients by week 8 of therapy and in 50%-60% of tested patients during follow-up. An average of 17.9 HCRU visits were reported during the study period. The most commonly used resources were nursing visits for routine follow-up. Conclusions: Results from this real-world study suggest that most patients were not treated according to the product monograph. Further studies are required to determine how oral treatments fit into this paradigm and how these findings extrapolate to the current treatment model. This study can serve as a benchmark for future real-world treatment including heath care utilization analyses.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".