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True-positive Reflex Threshold Value for HCV Antibody Screening Test

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Date 2022 Apr 11
PMID 35404859
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Abstract

Introduction: The use of a signal-to-cut-off ratio has been recommended by the Centre for Disease Control and Prevention to determine the need for further validation using a supplemental test. In this study, we aimed to determine the optimal true-positive signal-to-cut-off ratio for the ABBOTT ARCHITECT i2000SR immunoassay (Abbott Laboratories, Illinois, USA), using the Serodia® HCV particle agglutination (HCV-PA) assay (Fujirebio Inc, Tokyo, Japan) as the reference test for anti-HCV screening.

Methodology: We analysed a total of 13,240 specimens using the ARCHITECT i2000SR immunoassay and subsequently subjected all the reactive specimens with a signal-to-cut-off ratio ≥ 1.00 (n = 267) to the Serodia® HCV-PA reference assay. Receiver operating characteristic (ROC) curve analysis was carried out and performance characteristics for each signal-to-cut-off ratio were determined. The selected signal-to-cut-off ratio value was then assessed using a line immunoassay (LIA) test.

Results: ROC curve analysis determined that the optimal signal-to-cut-off ratio was 5.05, which gave the highest Youden's Index (J) value of 0.89, with a sensitivity of 93.1% (88.9-97.2), a specificity of 96.0% (92.4-99.4), a positive predictive value of 96.4% (93.3-99.5), and a negative predictive value of 92.2% (87.5-96.8). Validation of the optimal S/Co value using the LIA test yielded an accuracy of 91.8%, with sensitivity and specificity values of 92.0% and 91.7%, respectively.

Conclusions: The optimal signal-to-cut-off ratio value for the ARCHITECT i2000SR immunoassay, which was determined using HCV-PA assay as the reference test and validated using a HCV-LIA assay, showed high sensitivity and specificity, and may be used in routine anti-HCV screening.

Citing Articles

Seroprevalence of Transfusion Transmissible Infections and Associated Risk Factors in Hospitalized Patients before Transfusion in Jinling Hospital Nanjing University: A Three-Year Retrospective Study.

Wang W, Kong X, Zhao G, Huang X, Yuan J, Li N Pathogens. 2022; 11(6).

PMID: 35745563 PMC: 9227149. DOI: 10.3390/pathogens11060710.