A new mathematical model to identify contacts with recent and remote latent tuberculosis
Tuberculosis (TB) elimination programmes need to target preventive treatment to groups with an increased risk of TB activation, such as individuals with a latent tuberculosis infection (LTBI) acquired recently. Current diagnostic tests for LTBI have poor predictive values for TB activation and there...
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Published in | ERJ open research Vol. 5; no. 2; p. 78 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
England
European Respiratory Society
01.04.2019
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Subjects | |
Online Access | Get full text |
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Summary: | Tuberculosis (TB) elimination programmes need to target preventive treatment to groups with an increased risk of TB activation, such as individuals with a latent tuberculosis infection (LTBI) acquired recently. Current diagnostic tests for LTBI have poor predictive values for TB activation and there is, at present, no reference method to evaluate new LTBI diagnostic and prognostic tools. Thus, our objective was to develop a mathematical model, independent of currently available diagnostic tests, to estimate the individual probability of recent and/or remote LTBI. Estimations of recent LTBI were based on the contagiousness of index case, proximity and time of exposure, and environmental factors. Estimation of remote LTBI was based on country of origin, previous stays in high-risk environments or known exposure to TB. Individual probabilities were calculated and compared with tuberculin skin test (TST) and interferon-γ release assay results for 162 contacts of 42 index TB cases. Probabilities of remote LTBI were 16% for European/American contacts and 38% for African/Asian contacts. The probability of recent LTBI was 35% for close contacts to smear microscopy positive index cases. A higher probability of remote LTBI was seen among TST-positive contacts. This model may, with further validation, be used as an independent tool to evaluate new diagnostic markers for recent LTBI.
Karolinska Institutet and Stockholm County (grants K0190-2014 and K2017-4578. Funding information for this article has been deposited with the Crossref Funder Registry |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2312-0541 2312-0541 |
DOI: | 10.1183/23120541.00078-2019 |