Optimization and interpretation of serial QuantiFERON testing to measure acquisition of mycobacterium tuberculosis infection

Rationale: Conversion from a negative to positive QuantiFERONTB test is indicative of Mycobacterium tuberculosis (Mtb) infection, which predisposes individuals to tuberculosis disease. Interpretation of serial tests is confounded by immunological and technical variability. Objectives: To improve the consistency of serial QuantiFERON-TB testing algorithms and provide a data-driven definition of conversion. Methods: Sources of QuantiFERON-TB variability were assessed, and optimal procedures were identified. Distributions of IFN-g response levels were analyzed in healthy adolescents, Mtb-unexposed control subjects, and patients with pulmonary tuberculosis. Measurements and Main Results: Individuals with no known Mtb exposure had IFN-g values less than 0.2 IU/ml. Among individuals with IFN-g values less than 0.2 IU/ml, 0.2-0.34 IU/ml, 0.35-0.7 IU/ml, and greater than 0.7 IU/ml, tuberculin skin test positivity results were 15%, 53%, 66%, and 91% (P,0.005), respectively. Together, these findings suggest that values less than 0.2 IU/ml were true negatives. In short-term serial testing, "uncertain" conversions, with at least one value within the uncertainty zone (0.2-0.7 IU/ml), were partly explained by technical assay variability. Individuals who had a change in QuantiFERON-TB IFN-g values from less than 0.2 to greater than 0.7 IU/ml had 10-fold higher tuberculosis incidence rates than those who maintained values less than 0.2 IU/ml over 2 years (P = 0.0003).By contrast, "uncertain" converters were not at higher risk than nonconverters (P = 0.229). Eighty-seven percent of patients with active tuberculosis had IFN-g values greater than 0.7 IU/ml, suggesting that these values are consistent with established Mtb infection. Conclusions: Implementation of optimized procedures and a more rigorous QuantiFERON-TB conversion definition (an increase from IFN-g,0.2 to.0.7 IU/ml) would allow more definitive detection of recent Mtb infection and potentially improve identification of those more likely to develop disease.