J E Stout1, R Belknap2, Y-J Wu3, C S Ho4. 1. Division of Infectious Diseases and International Health, Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA. 2. Denver Health, Denver, Colorado, USA. 3. Northrop Grumman, Atlanta, Georgia, USA. 4. Field Services Branch, Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Abstract
SETTING: Serial screening for latent tuberculous infection (LTBI) is commonly performed in certain populations, such as health care workers. The high apparent conversion rate in some studies of interferon-gamma release assays is puzzling given the claimed high specificity of these tests. OBJECTIVE: To understand how test-retest variability, specificity, and underlying LTBI prevalence affect observed outcomes of repeated testing for LTBI. DESIGN: Mathematical model assuming constant test sensitivity and specificity over time and no new infections. RESULTS: Test-retest variability had a large effect on the observed proportion of conversions (initial negative test, followed by a positive test) and reversions (initial positive test, followed by a negative test). For example, a test with 70% specificity and 5% test-retest variability would be associated with a conversion rate of 3.7% and a reversion rate of 7.7%, while a test with 95% specificity but 10% test-retest variability would be associated with a conversion rate of 5.5% and a reversion rate of 57%, assuming that both tests are 80% sensitive and underlying LTBI prevalence was 5%. CONCLUSION: Test-retest variability is a key parameter that should be reported for tests used for serial screening for LTBI. Reducing test-retest variability can reduce false-positive and false-negative results.
SETTING: Serial screening for latent tuberculous infection (LTBI) is commonly performed in certain populations, such as health care workers. The high apparent conversion rate in some studies of interferon-gamma release assays is puzzling given the claimed high specificity of these tests. OBJECTIVE: To understand how test-retest variability, specificity, and underlying LTBI prevalence affect observed outcomes of repeated testing for LTBI. DESIGN: Mathematical model assuming constant test sensitivity and specificity over time and no new infections. RESULTS: Test-retest variability had a large effect on the observed proportion of conversions (initial negative test, followed by a positive test) and reversions (initial positive test, followed by a negative test). For example, a test with 70% specificity and 5% test-retest variability would be associated with a conversion rate of 3.7% and a reversion rate of 7.7%, while a test with 95% specificity but 10% test-retest variability would be associated with a conversion rate of 5.5% and a reversion rate of 57%, assuming that both tests are 80% sensitive and underlying LTBI prevalence was 5%. CONCLUSION: Test-retest variability is a key parameter that should be reported for tests used for serial screening for LTBI. Reducing test-retest variability can reduce false-positive and false-negative results.
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