An Analysis of Predictive Sample-to-Cutoff Index for HIV Infection Confirmation Using Elecsys® HIV Combi PT Assay. (10th August 2022)

• Record Type: Journal Article
• Authors: Xia, Xiaohong; Zhang, Xiang; Zhou, Jun; Zhang, Mengying
• Other Names: Cui Dawei Academic Editor.
• Is Part Of: International journal of clinical practice. Volume 2022(2022)
• Publication Date: 2022-08-10
• Subjects: Clinical medicine -- Periodicals; Medicine -- Periodicals; 610.5
• DOI: 10.1155/2022/5097189
• Languages: English
• ISSNs: 1368-5031

Abstract

Abstract : Background . Early and rapid diagnosis is crucial in HIV preventing and treatment. However, the false-positive rate (FPR) by 4-th generation detection assays was high in low-HIV-prevalence regions. Objectives . To analyze the relation between sample-to-cutoff index (COI) and HIV confirmatory results, and to explore a new COI threshold in our own laboratory to predict HIV infection. Methods . We retrospectively analyzed primarily reactive results by Elecsys® HIV combi PT assays and their confirmatory results by western blot (WB) at Nanjing Center for Disease Control and Prevention (CDC). The mean COI values of true positive (TP), false positive (FP), and indeterminate groups were compared, and receiver operating characteristic curve (ROC) analysis was performed to determine the optimal COI value for predicting HIV infection. Results . Totally 150, 980 HIV serological results were reviewed, and 305 (0.2%) were primarily reactive. There are 82 (26.89%) true positives, 210 (71.92%) false positives, and 11 indeterminate samples confirmed by WB tests, and another 2 patients rejected WB tests. Mean COI values of TP (643.5) were greatly higher than that of FP (3.174) (P < 0.0001 ), but there is no significant difference between FP and indeterminate groups. Combining the requirement of HIV diagnosis and ROC analysis, 9.87 was established as the optimal threshold to predict the infection, with 100% sensitivity and 99.99% specificity. Conclusions . By adjusting the COI threshold, the FP samples can be reduced and the efficiency of screening assays can be increased, which can save much additional reagent and staff costs and much time for delivery of HIV test results.