P139 Systematic review and meta-analysis of barriers and enablers to hepatitis C direct-acting antiviral treatment initiation
Bibliographic record
Abstract
Despite the successes of the direct-acting antiviral (DAA) programme for hepatitis C virus (HCV) infection, many groups still experience challenges to accessing care. We aimed to determine the barriers and enablers associated with hepatitis C DAA initiation and their relative impact. We performed a systematic review and meta-analysis of the barriers and enablers to HCV treatment initiation in the DAA era in high income settings with free universal healthcare. We searched eight bibliographic databases for studies published between 2014 and May 2022 using pre-defined keywords. We included quantitative studies investigating positive or negative associations with DAA treatment initiation. Data were extracted into a standardised form and a random-effects meta-analysis was conducted to pool the effects of variables on treatment initiation. The I2 statistic was used to measure heterogeneity across studies. Of 5198 articles identified, 42 studies conducted in Australia, Canada and Europe were included. Overall quality was ‘fair’ or ‘good’ in 37. Significant negative associations with DAA treatment included: unstable housing (14 studies, pooled odds ratio (OR) 0.48, 95% confidence interval (CI) 0.40–0.58, I2 = 21.1%); active injecting drug use (OR 0.54, CI 0.39–0.74, I2 = 97.5%); low income or socioeconomic status (seven studies, OR 0.75, CI 0.60–0.94, I2 = 73.7%) and female gender (26 studies, 0.78, CI 0.69–0.89, I2 = 89.9%). Positive associations included: increasing age (17 studies, OR 1.76, 95% CI 1.30–2.40, I2 = 95.4%); previous HCV treatment (nine studies, OR 2.20, CI 1.45–3.34, I2 = 85.8%); fibrosis stage (13 studies, OR 1.80, CI 1.15–2.79, I2 = 95.6%) and opioid substitution in people who inject drugs (12 studies, OR 1.54, 95% CI 1.15–2.05, I2 = 65.9%). There was no overall effect of high-risk alcohol use on treatment initiation when compared with lower (or no) alcohol use (13 studies, OR 0.91, 95% CI 0.64–1.27, I2 = 98.3%). The most impactful factors associated with DAA treatment initiation were socioeconomic and fixed demographic or disease characteristics. This should enable pre-emptive identification and intervention in those at risk of disengagement before treatment. Active injecting drug use was the only behavioural characteristic consistently associated with lower treatment initiation but this is significantly mitigated by opiate substitution therapy. References Doyle JS, Scott N, Sacks-Davis R, et al. Treatment access is only the first step to hepatitis C elimination: experience of universal anti-viral treatment access in Australia. Aliment Pharmacol Ther 2019;49:1223–9. Amoako A, Ortiz-Paredes D, Engler K, et al. Patient and provider perceived barriers and facilitators to direct acting antiviral hepatitis C treatment among priority populations in high income countries: a knowledge synthesis. Int J Drug Policy. 2021;96:103247. Hashim A, Macken L, Jones AM, et al. Community-based assessment and treatment of hepatitis C virus-related liver disease, injecting drug and alcohol use amongst people who are homeless: a systematic review and meta-analysis. Int J Drug Policy 2021;96:103342. Paisi M, Crombag N, Burns L, et al. Barriers and facilitators to hepatitis C screening and treatment for people with lived experience of homelessness: A mixed‐methods systematic review. Health Expect 2022;25:48–60.
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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 | 0.016 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.040 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".