The population level care cascade for hepatitis C in British Columbia, Canada as of 2018: Impact of direct acting antivirals
Bibliographic record
Abstract
BACKGROUND: Population-level monitoring of hepatitis C virus (HCV) infected people across cascades of care identifies gaps in access and engagement in care and treatment. We characterized the population-level care cascade for HCV in British Columbia (BC), Canada before and after introduction of Direct Acting Antiviral (DAA) treatment. METHODS: BC Hepatitis Testers Cohort (BC-HTC) includes 1.7 million individuals tested for HCV, HIV, reported cases of hepatitis B, and active tuberculosis in BC from 1990 to 2018 linked to medical visits, hospitalizations, cancers, prescription drugs and mortality data. We defined six HCV care cascade stages: (a) antibody diagnosed; (b) RNA tested; (c) RNA positive; (d) genotyped; (e) initiated treatment; and (f) achieved sustained virologic response (SVR). RESULTS: We estimated 61 127 people were HCV antibody positive in BC in 2018 (undiagnosed: 7686, 13%; diagnosed: 53 441, 87%). Of those diagnosed, 83% (44 507) had HCV RNA testing, and of those RNA positive, 90% (28 716) were genotyped. Of those genotyped, 61% (17 441) received therapy, with 90% (15 672) reaching SVR. Individuals from older birth cohorts had lower progression to HCV RNA testing. While people who currently inject drugs had the highest proportional progression to RNA testing, this group had the lowest proportional treatment uptake. CONCLUSIONS: Although gaps in HCV RNA and genotype testing after antibody diagnosis exist, the largest gap in the care cascade is treatment initiation, despite introduction of DAA treatment and removal of treatment eligibility restrictions. Further interventions are required to ensure testing and treatment is equitably accessible in BC.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".