Women in the 2019 hepatitis C cascade of care: findings from the British Columbia Hepatitis Testers cohort study
Bibliographic record
Abstract
Abstract Background Women living with hepatitis C virus (HCV) are rarely addressed in research and may be overrepresented within key populations requiring additional support to access HCV care and treatment. We constructed the HCV care cascade among people diagnosed with HCV in British Columbia, Canada, as of 2019 to compare progress in care and treatment and to assess sex/gender gaps in HCV treatment access. Methods The BC Hepatitis Testers Cohort includes 1.7 million people who tested for HCV, HIV, reported cases of hepatitis B, and active tuberculosis in BC from 2000 to 2019. Test results were linked to medical visits, hospitalizations, cancers, prescription drugs, and mortality data. Six HCV care cascade stages were identified: (1) antibody diagnosed; (2) RNA tested; (3) RNA positive; (4) genotyped; (5) initiated treatment; and (6) achieved sustained virologic response (SVR). HCV care cascade results were assessed for women, and an ‘inverse’ cascade was created to assess gaps, including not being RNA tested, genotyped, or treatment initiated, stratified by sex. Results In 2019, 52,638 people with known sex were anti-HCV positive in BC; 37% (19,522) were women. Confirmatory RNA tests were received by 86% (16,797/19,522) of anti-HCV positive women and 83% (27,353/33,116) of men. Among people who had been genotyped, 68% (6756/10,008) of women and 67% (12,640/18,828) of men initiated treatment, with 94% (5023/5364) of women and 92% (9147/9897) of men achieving SVR. Among the 3252 women and 6188 men not yet treated, higher proportions of women compared to men were born after 1975 (30% vs. 21%), had a mental health diagnosis (42% vs. 34%) and had used injection drugs (50% vs. 45%). Among 1619 women and 2780 men who had used injection drugs and were not yet treated, higher proportions of women than men used stimulants (64% vs. 57%), and opiates (67% vs. 60%). Conclusions Women and men appear to be equally engaged into the HCV care cascade; however, women with concurrent social and health conditions are being left behind. Treatment access may be improved with approaches that meet the needs of younger women, those with mental health diagnoses, and women who use drugs.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".