The Population Level Cascade of Care for Hepatitis C in British Columbia, Canada: The BC Hepatitis Testers Cohort (BC-HTC)
Bibliographic record
Abstract
BACKGROUND: Population-level monitoring of hepatitis C virus (HCV) infected people across the cascade of care identifies gaps in access and engagement in care and treatment. We characterized a population-level cascade of care for HCV in British Columbia (BC), Canada and identified factors associated with leakage at each stage. METHODS: The BC Hepatitis Testers Cohort (BC-HTC) includes 1.5million individuals tested for HCV, HIV, reported cases of hepatitis B, and active tuberculosis in BC from 1990 to 2013 linked to medical visits, hospitalizations, cancers, prescription drugs and mortality data. We defined six HCV cascade of care stages: 1) estimated population prevalence; 2) HCV diagnosed; 3) HCV RNA tested; 4) genotyped; 5) initiated treatment; and 6) achieved sustained virologic response (SVR). RESULTS: We estimated that 73,203 people were HCV antibody positive in BC in 2012 (undiagnosed: 18,301, 25%; diagnosed: 54,902, 75%). Of these, 56%(40,656) had HCV RNA testing; 34%(26,300) were genotyped; 12%( 8532 ) had received interferon-based therapy and 7%(5197) had SVR. Males, older birth cohorts, and HBV coinfected were less likely to undergo HCV RNA testing. Among those with chronic HCV infection, 32% had received liver-related care. Retention in liver care was more likely in those with HIV, cirrhosis, and drug/alcohol use and less likely in males and HBV coinfected. CONCLUSIONS: Although there are gaps in HCV RNA testing and genotyping after HCV diagnosis, the major gap in the cascade of care was low treatment initiation. People with comorbidities progressed through the cascade of testing and care but few received treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".