Ongoing Gaps in the Hepatitis C Care Cascade during the Direct-Acting Antiviral Era in a Large Retrospective Cohort in Canada: A Population-Based Study
Bibliographic record
Abstract
To achieve hepatitis C virus (HCV) elimination, high uptake along the care cascade steps for all will be necessary. We mapped engagement with the care cascade overall and among priority groups in the post-direct-acting antivirals (DAAs) period and assessed if this changed relative to pre-DAAs. We created a population-based cohort of all reported HCV diagnoses in Quebec (1990-2018) and constructed the care cascade [antibody diagnosed, RNA tested, RNA positive, genotyped, treated, sustained virologic response (SVR)] in 2013 and 2018. Characteristics associated with RNA testing and treatment initiation were investigated using marginal logistic models via generalized estimating equations. Of the 31,439 individuals HCV-diagnosed in Quebec since 1990 and alive as of 2018, there was significant progress in engagement with the care cascade post- vs. pre-DAAs; 86% vs. 77% were RNA-tested, and 64% vs. 40% initiated treatment. As of 2018, a higher risk of not being RNA-tested or treated was observed among individuals born <1945 vs. >1965 [hazard ratio (HR); 95% CI; 1.35 (1.16-1.57)], those with material and social deprivation [1.21 (1.06-1.38)], and those with alcohol use disorder [1.21 (1.08-1.360]. Overall, non-immigrants had lower rates of RNA testing [0.76 (0.67-0.85)] and treatment initiation [0.63 (0.57-0.70)] than immigrants. As of 2018, PWID had a lower risk of not being RNA tested [0.67 (0.61-0.85)] but a similar risk of not being treated, compared to non-PWID. Engagement in the HCV care cascade have improved in the post-DAA era, but inequities remain. Vulnerable subgroups, including certain older immigrants, were less likely to have received RNA testing or treatment as of 2018 and would benefit from focused interventions to strengthen these steps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".