Assessment of novel rapid assays to accurately diagnose Hepatitis C Virus infection

Abstract

The World Health Organization (WHO) estimates that more than 185 million people globally are infected with HCV of whom 350,000 people die annually. The diagnosis of HCV is based primarily on the use of assays that require instrumentation and cannot be performed in point of care venues. Rapid and novel HCV tests are being introduced that offer advantages, including the use of oral fluids, and some that can detect HIV and HCV simultaneously. The objectives of this study are: (1) to evaluate the diagnostic sensitivity, specificity and reproducibility of four rapid tests for the accurate detection of HCV, and noting the reactivity to HIV in those tests offering multi-agent detection; (2) to determine if an HCV rapid testing algorithm can be devised using two or more of these rapid tests that provides better accuracy than one test alone, (3) to compare other characteristics of the tests such as line intensity, slow flow through, partial lines, the impact of sample integrity, and clearance of background for easy test result reading; and (4) to evaluate the tests by comparing results when read by two observers. Four rapid HCV assays, including the OraQuick®HCV Rapid Test, the Chembio DPP HIV-HCV Assay, the Chembio DPP HCV Assay, and the Multiplo rapid HBc/HIV/HCV antibody test, were assessed to determine their ability to accurately diagnose HCV in 204 archived plasma samples. The sensitivity and specificity were determined by comparing the results obtained from the candidate assays to those of an FDA approved ELISA. Reproducibility was evaluated by running one weakly reactive and one non-reactive sample on the tests for ten consecutive days and comparing the results to the reference method. The specificity of three tests was 100%, while that of one test was 98% (one false positive). The sensitivity for all four tests was 100%, and the reproducibility of all was excellent. One of the two tests that also detects HIV produced perfect results. Further studies, using a larger sample size, are needed to verify these results and evaluate an algorithm.