ABSTRACT
BACKGROUND/AIMS: Hepatitis C Virus (HCV) infection is diagnosed by the presence of antibody to HCV and/or HCV RNA. This study aimed to evaluate the accuracy of anti-HCV titer (S/CO ratio) in predicting HCV viremia in patients with or without hepatitis B virus (HBV) dual infection. METHODS: Anti-HCV seropositive patients who were treatment-naïve consecutively enrolled. Anti-HCV antibodies were detected using a commercially chemiluminescent microparticle immunoassay. HCV RNA was detected by real-time PCR method. RESULTS: A total of 1321 including1196 mono-infected and 125 HBV dually infected patients were analyzed. The best cut-off value of anti-HCV titer in predicting HCV viremia was 9.95 (AUROC 0.99, P<0.0001). Of the entire cohort, the anti-HCV cut-off value of 10 provided the best accuracy, 96.8%, with the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 96.3%, 98.9%, 99.7% and 87.3% respectively. The best cut-off value of anti-HCV titer in predicting HCV viremia was 9.95 (AUROC 0.99, P<0.0001) and 9.36 (AUROC 1.00, P<0.0001) in patients with HCV mono-infection and HBV dual-infection respectively. Among the HBV dually infected patients, the accuracy of anti-HCV titer in predicting HCV viremia reached up to 100% with the cut-off value of 9. All the patients were HCV-viremic if their anti-HCV titer was greater than 9 (PPV 100%). On the other hand, all the patients were HCV non-viremic if their anti-HCV titer was less than 9 (NPV 100%). CONCLUSIONS: Anti-HCV titer strongly predicted HCV viremia. This excellent performance could be generalized to either HCV mono-infected or HBV dually infected patients.
Subject(s)
Hepatitis B virus/isolation & purification , Hepatitis B/blood , Hepatitis C Antibodies/blood , Hepatitis C/blood , Aged , Female , Hepacivirus/isolation & purification , Hepacivirus/pathogenicity , Hepatitis B/genetics , Hepatitis B/pathology , Hepatitis B virus/pathogenicity , Hepatitis C/pathology , Hepatitis C/virology , Humans , Male , Middle Aged , Predictive Value of Tests , RNA, Viral , Serologic TestsABSTRACT
BACKGROUND AND AIMS: Hepatitis C virus (HCV) genotyping is a pivotal tool for epidemiological investigation, guiding management and antiviral treatment. Challenge existed in identifying subtypes of genotype-1 (G-1) and genotype (GT) of indeterminate. Recently, the Abbott HCV RealTime Genotype Plus RUO assay (HCV GT Plus) has been developed aiming to overcome the limitations. We aimed to evaluate the performance of the assay compared with 5' UTR sequencing in clinical samples. MATERIALS AND METHODS: Eligible individuals were treatment chronic hepatitis C patients that were enrolled consecutively in a medical center and two core regional hospitals in southern Taiwan from Oct 2017 through Aug 2018. The patient with genotype 1 without subtype and indeterminate previously genotyped by Abbott RealTime HCV GT II will further determinate by Abbott HCV RealTime HCV GT Plus. All of the genotype results were validated by 5' UTR sequencing as a reference standard. RESULTS: A total of 100 viremic CHC patients were recruited, including 63 G-1 patients (male: 28), and 37 patients (male: 15) of indeterminate genotyped by Abbott RealTime HCV GT II assay (HCV GT II), respectively. The detection rate of 63 GT1 samples without subtype were 93.7% (59/63), 37 indeterminate samples without genotype were 62.2 (23/37) by HCV GT Plus. 5' UTR sequencing confirmed HCV GT Plus characterized results for 84.7% (50/59) of type1, with 100% (4/4), 82.8 (24/29) and 84.6% (22/26) for 1a, 1b and type6; 65.2% (15/23) of indeterminate with 100% (3/3) and 60% (12/20) for 1b and type 6 samples, respectively. CONCLUSIONS: The Abbott RealTime HCV GT Plus RUO assay provides additional performance in GT detection.
Subject(s)
Genotype , Genotyping Techniques , Hepacivirus/genetics , Hepatitis C/genetics , Real-Time Polymerase Chain Reaction , Viremia/genetics , Aged , Female , Hepatitis C/epidemiology , Humans , Male , Middle Aged , Taiwan/epidemiologyABSTRACT
BACKGROUND/AIMS: Obstacles exist in facilitating hepatitis C virus (HCV) care cascade. To increase timely and accurate diagnosis, disease awareness and accessibility, in-hospital HCV reflex testing followed by automatic appointments and a late call-back strategy (R.N.A. model) was applied. We aimed to compare the HCV treatment rate of patients treated with this strategy compared to those without. METHODS: One hundred and twenty-five anti-HCV seropositive patients who adopted the R.N.A. model in 2020 and another 1,396 controls treated in 2019 were enrolled to compare the gaps in accurate HCV RNA diagnosis to final treatment allocation. RESULTS: The HCV RNA testing rate was significantly higher in patients who received reflex testing than in those without reflex testing (100% vs. 84.8%, P<0.001). When patients were stratified according to the referring outpatient department, a significant improvement in the HCV RNA testing rate was particularly noted in patients from non-hepatology departments (100% vs. 23.3%, P<0.001). The treatment rate in HCV RNA seropositive patients was 83% (83/100) after the adoption of the R.N.A. model, among whom 96.1% and 73.9% of patients were from the hepatology and non-hepatology departments, respectively. Compared to subjects without R.N.A. model application, a significant improvement in the treatment rate was observed for patients from non-hepatology departments (73.9% vs. 27.8%, P=0.001). The application of the R.N.A. model significantly increased the in-hospital HCV treatment uptake from 6.4% to 73.9% for patients from non-hepatology departments (P<0.001). CONCLUSION: The care cascade increased the treatment uptake and set up a model for enhancing in-hospital HCV elimination.
