Resistance‐Associated Substitution Testing Trends and Impact on <scp>HCV</scp> Treatment Outcomes in Canada: A <scp>CanHepC</scp>‐<scp>CANUHC</scp> Analysis
Bibliographic record
Abstract
Resistance-associated substitutions (RASs) are mutations within the hepatitis C (HCV) genome that may influence the likelihood of achieving a sustained virological response (SVR) with direct acting antiviral (DAA) treatment. Clinicians conduct RAS testing to adapt treatment regimens with the intent of improving the likelihood of cure. The Canadian Network Undertaking against Hepatitis C (CANUHC) prospective cohort consists of chronic HCV patients enrolled between 2015 and 2023 across 17 Canadian sites. Utilisation of RAS testing was assessed across demographics, clinical characteristics and years. SVR was described for the overall cohort and compared across populations of patients with historically negative predictors of SVR. The detection of key RASs and how this information influenced DAA selection were assessed. 2434 patients were identified with information on RAS testing. 98.3% achieved SVR. Out of the 227 patients tested for RAS, 147 (64.8%) had any detected RAS, and 84 (37.0%) had an NS5A RAS. The proportion of patients with SVR did not differ between RAS-tested (98.3%) and non-tested patients (98.3%; p = 0.99). SVR in those with an NS5a RAS was similar (98.6%) to the overall SVR proportion. Proportions with SVR did not differ between those with and without RAS testing in key subgroups (genotype 1a, genotype 3, prior treatment, cirrhosis). The specific DAA regimen and the addition of ribavirin were not associated with SVR outcome. RAS testing has a minimal influence on antiviral treatment selection. Going forward, there is a reduced role for RAS testing in most clinical scenarios.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".