Using signal-to-cutoff ratios of HIV screening assay to predict HIV infection.

BACKGROUND: The sensitivity of HIV screening assays often leads to a high rate of false-positive results, requiring retests and confirmatory tests. This study aimed to analyze the capability of signal-to-cutoff (S/CO) ratios of HIV screening assay to predict HIV infection. METHODS: A retrospective study on the HIV screening-positive population was performed at Zhongshan Hospital, Xiamen University, the correlation between HIV screening assay S/CO ratios and HIV infection was assessed, and plotted Receiver Operating Characteristic (ROC) curves were generated to establish the optimal cutoff value for predicting HIV infection. RESULTS: Out of 396,679 patients, 836 were confirmed to be HIV-infected, with an HIV prevalence of 0.21%. The median S/CO ratios in HIV infection were significantly higher than that in non-HIV infection (296.9 vs. 2.41, P < 0.001). The rate of confirmed HIV infection was increased with higher S/CO ratios in the screening assay. The ROC curve based on the HIV screening assay S/CO ratio achieved a sensitivity of 93.78% and a specificity of 93.12% with an optimal cutoff value of 14.09. The area under the ROC curve was 0.9612. Further analysis of the ROC curve indicated that the S/CO ratio thresholds yielding positive predictive values of 99%, 99.5%, and 100% for HIV infection were 26.25, 285.7, and 354.5, respectively. CONCLUSION: Using HIV screening assay S/CO ratio to predict HIV infection can largely reduce necessitating retests and confirmatory tests. Incorporating the S/CO ratio into HIV testing algorithms can have significant implications for medical and public health practices.

Analysis of the characteristics of patients with false-positive HIV screening assay results.

OBJECTIVE: To investigate the clinical characteristics of patients with false-positive human immunodeficiency virus (HIV) screening test results and provide a theoretical basis to interpret the results of HIV screening tests. METHODS: This retrospective study evaluated the incidence of false-positive results for HIV screening tests and characterized false-positive reactions during HIV screening in a large-scale study at Zhongshan Hospital, Xiamen University. RESULTS: False-positive HIV test results occurred for 264 of 275,263 (0.10%) serum samples. Although the incidence of a false-positive HIV screening result did not differ between male and female patients (screening χ2 = 1.194; P = 0.275), it increased with age (χ2 = 25.759; P < 0.01). False-positive reactions were associated with 16 disease categories, including 101 diseases, some of which have never been reported previously to be associated with false-positive HIV screening results. CONCLUSIONS: The occurrence of false-positive HIV screening test results may indicate underlying serious disorders. Characterization of patients with false-positive HIV screening test results can help identify potential diseases unrelated to HIV.