![]() Information on DAA class resistance following treatment failure can provide insights on retreatment strategies. ![]() Interestingly, the NS5B_DSV RAS prevalence was 0% (0/22) pre-treatment vs. There was no major difference in pre- and post-treatment NS5B_SOF RAS frequencies ( Fig. 1C). ![]() Similarly, a notable difference of NS5A RAS prevalence was seen in GT1a (74% vs. Compared to DAA-naïve patients, the frequencies of NS3 RASs following DAA exposure were significanlty higher in GTs 1a (64% vs. About 34–42% of GT1 patients who failed DSV had detectable NS5B_DSV RAS. The RAS prevalence varied among GTs in patients who failed NS5AI-, PI- or SOF-containing regimens: 35–100% in NS3, 74–100% in NS5A, and 0–47% in NS5B (NS5B_SOF), respectively ( Fig. 1). ASV, asunaprevir BOC, boceprevir DAA, direct-acting antiviral DCV, daclatasvir DSV, dasabuvir EBR, elbasvir GLE, glecaprevir GT, genotype GT1-other, any GT1 subtypes except GT1a and GT1b GZR, grazoprevir LDV, ledipasvir NA, not available NI, nucleoside inhibitor NNI, non-nucleoside inhibitor NS5AI, NS5A inhibitor OMB, ombitasvir PAR/r, paritaprevir/ritonavir PI, protease inhibitor PIB, pibrentasvir RAS(s), resistance-associated substitution(s) SIM, simeprevir SOF, sofosbuvir TVR, telaprevir VEL, velpatasvir VOX, voxilaprevir. Patients who harbored ≥1 RAS variant listed in the 2020 EASL recommendations on treatment of hepatitis C were counted. HCV DAA-naïve patients were included to estimate the natural RAS prevalence. HCV sequences from virologic failures treated with combination regimens containing a PI (SIM, GZR, PAR/r, GLE, ASV, VOX, BOC, TVR), an NS5AI (LDV, DCV, EBR, VEL, OMB, PIB), or an NI (SOF)/NNI (DSV) were evaluated for the prevalence of RASs in NS3, NS5A, NS5B_SOF, and NS5B_DSV, respectively. A p value <0.05 was considered statistically significant. ![]() The analysis was performed using Stata v14.0 (StataCorp, College Station, Texas). Missing data was assessed as its own category for all hypothesized predictor variables with less than 90% data availability. All included variables were considered for multivariate logistic regression models to generate adjusted odds ratios (aORs) except injection drug use due to incomplete data. Unadjusted logistic regression analyses were performed to estimate odds ratios (ORs) and corresponding 95% CIs to identify factors associated with the presence of RASs in those who experienced treatment failure. The definition of cirrhosis was based on the classification used by each of the participating centers. Participants with a history of injection drug use (past and recent) were categorized as people who inject drugs. The age of the cohort was divided into quartiles (<52, 52–58, 58–63, and ≥64). Independent variables considered included sex, age, injection drug use, HIV coinfection, cirrhosis, DAA regimen, treatment history, and HCV genotype. Patients who had ≥1 RAS variant of the respective drug target gene per the 2020 EASL recommendations were considered as harboring RAS(s). We assessed factors associated with the presence of NS3 and NS5A RASs in sequences collected after treatment among people who failed PI and NS5A therapy, respectively, with separate models evaluating people receiving PI-based and NS5A-based therapies.
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