Abstract

BackgroundThe QuantiFERON®-TB Gold In-Tube test (QFT-GIT) detects Mycobacterium tuberculosis (Mtb) infection by measuring release of interferon gamma (IFN-γ) when T-cells (in heparinized whole blood) are stimulated with specific Mtb antigens. The amount of IFN-γ is determined by enzyme-linked immunosorbent assay (ELISA). Automation of the ELISA method may reduce variability. To assess the impact of ELISA automation, we compared QFT-GIT results and variability when ELISAs were performed manually and with automation.MethodsBlood was collected into two sets of QFT-GIT tubes and processed at the same time. For each set, IFN-γ was measured in automated and manual ELISAs. Variability in interpretations and IFN-γ measurements was assessed between automated (A1 vs. A2) and manual (M1 vs. M2) ELISAs. Variability in IFN-γ measurements was also assessed on separate groups stratified by the mean of the four ELISAs.ResultsSubjects (N = 146) had two automated and two manual ELISAs completed. Overall, interpretations were discordant for 16 (11%) subjects. Excluding one subject with indeterminate results, 7 (4.8%) subjects had discordant automated interpretations and 10 (6.9%) subjects had discordant manual interpretations (p = 0.17). Quantitative variability was not uniform; within-subject variability was greater with higher IFN-γ measurements and with manual ELISAs. For subjects with mean TB Responses ±0.25 IU/mL of the 0.35 IU/mL cutoff, the within-subject standard deviation for two manual tests was 0.27 (CI95 = 0.22–0.37) IU/mL vs. 0.09 (CI95 = 0.07–0.12) IU/mL for two automated tests.ConclusionQFT-GIT ELISA automation may reduce variability near the test cutoff. Methodological differences should be considered when interpreting and using IFN-γ release assays (IGRAs).

Highlights

  • The QuantiFERONH-TB Gold In-Tube test (QFT-GIT) was designed to detect Mycobacterium tuberculosis (Mtb) infection by quantifying the amount of interferon-c (IFN-c) released when whole blood is stimulated with specific Mtb antigens [1]

  • 0.85 0.80 0.84 0.73 0.74 0.90 multichannel pipetters (Rainin Instrument, LLC, Oakland, CA); plates were washed with a Biotrak II Microplate washer (Biochrom, Ltd., Cambridge, UK) in the Centers for Disease Control and Prevention (CDC) lab and a Dynex Ultrawash Plus Microplate washer (Dynex Technologies, Chantilly, VA) in the USAF lab; and optical densities (ODs) were measured with a Thermo Scientific, Multiskan Ascent (Waltham, MA) in the CDC lab and a BioTek ELX800 microplate reader (BioTek Instruments, Inc., Winooshi, VT) in the USAF lab

  • Five additional indices of quantitative variability were examined for each pair of enzyme-linked immunosorbent assay (ELISA), the last two of which were derived from the standard deviation of the differences (SDdiff): (1) within-subject coefficient of variation (W-S CV%), (2) intraclass correlation coefficient (ICC), (3) mean difference, (4) the smallest detectable difference (SDD), and (5) the within-subject standard deviation (W-S SD)

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Summary

Introduction

The QuantiFERONH-TB Gold In-Tube test (QFT-GIT) was designed to detect Mycobacterium tuberculosis (Mtb) infection by quantifying the amount of interferon-c (IFN-c) released when whole blood is stimulated with specific Mtb antigens [1]. The amount of IFN-c released is determined by enzyme-linked immunosorbent assay (ELISA). QFT-GIT and other IFN-c release assays (IGRAs) are alternatives to the tuberculin skin test (TST) for detecting Mtb infection, both latent infection (LTBI) and infection manifesting as active disease. Assessments of QFT-GIT repeatability and reproducibility have demonstrated appreciable amounts of variability [20,21]. The QuantiFERONH-TB Gold In-Tube test (QFT-GIT) detects Mycobacterium tuberculosis (Mtb) infection by measuring release of interferon gamma (IFN-c) when T-cells (in heparinized whole blood) are stimulated with specific Mtb antigens. The amount of IFN-c is determined by enzyme-linked immunosorbent assay (ELISA). To assess the impact of ELISA automation, we compared QFT-GIT results and variability when ELISAs were performed manually and with automation

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