The Signal-to-cutoff Ratios to Predict HCV Infection Among People Who Inject Drugs

People who inject drugs (PWIDs) are primarily the high-risk population for HCV infection. This study aims to determine the optimal cut-off values for predicting HCV infection status based on the Signal-to-Cutoff (S/CO) ratio. In this study, a total of 719 PWIDs' samples were collected, and performed for screening test by ELISA assay, and followed by RIBA assay and NAT assay to detect HCV antibody and HCV RNA levels, respectively. The findings revealed that the prevalence of HCV infection among PWIDs was 54.66% (393/719), and the false-positive rate of HCV antibody detection by ELISA assay among PWIDs was only 3.85% (16/416). In addition, when the optimal cut-off value for S/CO ratio was 2.0, the sensitivity and specificity of HCV antibody were 100.00% and 93.55%, respectively. And when the optimal cut-off value for S/CO ratio was 21.36, the sensitivity and specificity of HCV RNA positive were 89.90% and 72.73%, respectively. In conclusion, the status of HCV infection can be predicted based on the S/CO ratios of the ELISA assay, which can improve diagnosis and facilitate timely treatment to effectively prevent the spread of HCV infection.