Bayesian evaluation of the human immunodeficiency virus antibody screening strategy of duplicate enzyme-linked immunosorbent assay in Xuzhou Blood Center, China

BACKGROUND: Accurate estimation of the risk of human immunodeficiency virus (HIV) infection through transfusion is essential for monitoring blood safety. The risk, however, is so low that it can only be estimated by mathematical modeling. With the Bayesian dependence model, this study evaluates the HIV antibody screening strategy of duplicate enzyme-linked immunosorbent assay (ELISA) in Xuzhou Blood Center and therefore estimates part of the total risks of transfusion-transmitted HIV infection. STUDY DESIGN AND METHODS: Data from Xuzhou Blood Center between 2004 and 2008 were used. Information was obtained on donor profiles and screening and confirmatory test results. The portion of the risks of HIV infection through transfusion concerned was estimated by evaluating the screening algorithm in terms of its accuracy and predictive power with the Bayesian dependence model. RESULTS: A total of 234,602 donations from voluntary blood donors in Xuzhou Blood Center were screened for HIV antibody. For the study screening algorithm, its sensitivity, specificity, false-positive predictive value (FPPV), and false-negative predictive value (FNPV) were 0.9951 (95% Bayesian credible interval [BCI], 0.9763-0.9997), 0.9991 (95% BCI, 0.9990-0.9992), 0.9647 (95% BCI, 0.9018-0.9923), and 1.52 x 10-7 (95% BCI, 7.31 x 10-9-1.15 x 10-6), respectively. For the positive detection rate (9.60 x 10-4) and FPPV (0.9647), the differences between their own Bayesian median estimates and real values were 2.70 x 10-5 and -0.0033, respectively. CONCLUSIONS: The HIV antibody screening algorithm of duplicate ELISA is well evaluated in its accuracy and predictive power with the Bayesian dependence model. The FNPV measures the part of the risks of transfusion-associated HIV transmission concerned.