Automation of an interferon-γ release assay and comparison to the tuberculin skin test for screening basic military trainees for Mycobacterium tuberculosis infection.

We automated portions of the QuantiFERON-TB Gold In-Tube test (QFT-GIT) and assessed its quality when performed concurrently with the tuberculin skin test (TST) among U.S. Air Force basic military trainees (BMTs). The volume of blood collected for QFT-GIT was monitored. At least one of the three tubes required for QFT-GIT had blood volume outside the recommended 0.8- to 1.2-mL range for 688 (29.0%) of 2,373 subjects who had their blood collected. Of the 2,124 subjects who had TST and QFT-GIT completed, TST was positive for 0.6%; QFT-GIT was positive for 0.3% and indeterminate for 2.0%. Among 2,081 subjects with completed TST and determinate QFT-GIT results, overall agreement was 99.5% but positive agreement was 5.6%. Specificity among the 1,546 low-risk BMTs was identical (99.7%). Indeterminate QFT-GIT results were 2.7 times more likely when mitogen tubes contained >1.2 mL blood than when containing 0.8- to 1.2-mL blood. Automation can facilitate QFT-GIT completion, especially if the recommended volume of blood is collected. Mycobacterium tuberculosis infection prevalence among BMTs based on TST and QFT-GIT is similar and low. Selectively testing those with significant risk may be more appropriate than universal testing of all recruits.

Variability of the QuantiFERON®-TB gold in-tube test using automated and manual methods.

BACKGROUND: The 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. METHODS: Blood 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. RESULTS: Subjects (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. CONCLUSION: QFT-GIT ELISA automation may reduce variability near the test cutoff. Methodological differences should be considered when interpreting and using IFN-γ release assays (IGRAs).

Within-subject interlaboratory variability of QuantiFERON-TB gold in-tube tests.

BACKGROUND: The QuantiFERON®-TB Gold In-Tube test (QFT-GIT) is a viable alternative to the tuberculin skin test (TST) for detecting Mycobacterium tuberculosis infection. However, within-subject variability may limit test utility. To assess variability, we compared results from the same subjects when QFT-GIT enzyme-linked immunosorbent assays (ELISAs) were performed in different laboratories. METHODS: Subjects were recruited at two sites and blood was tested in three labs. Two labs used the same type of automated ELISA workstation, 8-point calibration curves, and electronic data transfer. The third lab used a different automated ELISA workstation, 4-point calibration curves, and manual data entry. Variability was assessed by interpretation agreement and comparison of interferon-γ (IFN-γ) measurements. Data for subjects with discordant interpretations or discrepancies in TB Response >0.05 IU/mL were verified or corrected, and variability was reassessed using a reconciled dataset. RESULTS: Ninety-seven subjects had results from three labs. Eleven (11.3%) had discordant interpretations and 72 (74.2%) had discrepancies >0.05 IU/mL using unreconciled results. After correction of manual data entry errors for 9 subjects, and exclusion of 6 subjects due to methodological errors, 7 (7.7%) subjects were discordant. Of these, 6 (85.7%) had all TB Responses within 0.25 IU/mL of the manufacturer's recommended cutoff. Non-uniform error of measurement was observed, with greater variation in higher IFN-γ measurements. Within-subject standard deviation for TB Response was as high as 0.16 IU/mL, and limits of agreement ranged from -0.46 to 0.43 IU/mL for subjects with mean TB Response within 0.25 IU/mL of the cutoff. CONCLUSION: Greater interlaboratory variability was associated with manual data entry and higher IFN-γ measurements. Manual data entry should be avoided. Because variability in measuring TB Response may affect interpretation, especially near the cutoff, consideration should be given to developing a range of values near the cutoff to be interpreted as "borderline," rather than negative or positive.