Cross-platform analysis of HIV-1 RNA data generated by a multicenter assay validation study with wide geographic representation

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Abstract

HIV-1 RNA quantitation continues to be extremely important for monitoring patients infected with HIV-1, and a number of assays have been utilized for this purpose. Differences in assay performance with respect to log10 recovery and HIV-1 subtype specificity have been well documented for commercially available assays, although comparisons are usually limited to one or two assay platforms. Two new FDA-approved assays, the Roche Cobas AmpliPrep/Cobas TaqMan HIV-1 test (RT) and the Abbott RealTime HIV-1 assay (AR), that utilize real-time PCR have replaced previous HIV-1 RNA platforms. Inadequate detection of some strains of HIV-1 resulted in the addition of a new primer/probe set and the introduction of a second version of the RT assay. In this study, comparisons of assay performance between the different FDA-approved HIV-1 RNA assay platforms (both new and existing) were performed by using validation data that included both well-characterized virus stock and locally collected clinical samples. Laboratories across diverse geographical regions performed the validation testing and submitted data to the Virology Quality Assurance program (VQA) for analysis. Correlation values for clinical sample testing varied across the assay platforms (r = 0.832 to 0.986), and average log10 recoveries for HIV-1 RNA controls (compared to the nominal value) ranged from -0.215 to 0.181. These data demonstrate the need for use of one assay platform for longitudinal patient monitoring, but the data also reinforce the notion that no one assay is superior and that testing across platforms may be required for discordance reconciliation. Copyright © 2012, American Society for Microbiology. All Rights Reserved.

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Jennings, C., Harty, B., Granger, S., Wager, C., Crump, J. A., Fiscus, S. A., & Bremer, J. W. (2012). Cross-platform analysis of HIV-1 RNA data generated by a multicenter assay validation study with wide geographic representation. Journal of Clinical Microbiology, 50(8), 2737–2747. https://doi.org/10.1128/JCM.00578-12

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