Journal
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
Volume 201, Issue 8, Pages 984-991Publisher
AMER THORACIC SOC
DOI: 10.1164/rccm.201905-0969OC
Keywords
latent tuberculosis; epidemiology; screening; QuantiFERON; T-SPOT.TB
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Funding
- Wellcome Trust [207511/Z/17/Z] Funding Source: Wellcome Trust
- Medical Research Council Funding Source: Medline
- Wellcome Trust [207511/Z/17/Z] Funding Source: Medline
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Rationale: Development of diagnostic tools with improved predictive value for tuberculosis (TB) is a global research priority. Objectives: We evaluated whether implementing higher diagnostic thresholds than currently recommended for QuantiFERON Gold-in-Tube (QFT-GIT), T-SPOT.TB, and the tuberculin skin test (TST) might improve prediction of incident TB. Methods: Follow-up of a UK cohort of 9,610 adult TB contacts and recent migrants was extended by relinkage to national TB surveillance records (median follow-up 4.7 yr). Incidence rates and rate ratios, sensitivities, specificities, and predictive values for incident TB were calculated according to ordinal strata for quantitative results of QFT-GIT, T-SPOT.TB, and TST (with adjustment for prior bacillus Calmette-Guerin [BCG] vaccination). Measurements and Main Results: For all tests, incidence rates and rate ratios increased with the magnitude of the test result (P < 0.0001). Over 3 years' follow-up, there was a modest increase in positive predictive value with the higher thresholds (3.0% for QFT-GIT >= 0.35 IU/ml vs. 3.6% for >= 4.00 IU/ml; 3.4% for T-SPOT.TB spots vs. >= 5.0% for >= 50 spots; and 3.1% for BCG-adjusted TST >= 5 mm vs. 4.3% for >= 15 mm). As thresholds increased, sensitivity to detect incident TB waned for all tests (61.0% for QFT-GIT >= 0.35 IU/ml vs. 23.2% for >= 4.00 IU/ml; 65.4% for T-SPOT.TB >= 5 spots vs. 27.2% for spots; 69.7% for BCG-adjusted TST >= 5 mm vs. 28.1% for >= 15mm). Conclusions: Implementation of higher thresholds for QFT-GIT, T-SPOT.TB, and TST modestly increases positive predictive value for incident TB, but markedly reduces sensitivity. Novel biomarkers or validated multivariable risk algorithms are required to improve prediction of incident TB.
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