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Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda

One principle of tuberculosis control is to prevent the development of tuberculosis disease by treating individuals with latent tuberculosis infection. The diagnosis of latent infection using the tuberculin skin test is not straightforward because of concerns about immunologic cross reactivity with...

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Autores principales: Woldu, Henok G., Zalwango, Sarah, Martinez, Leonardo, Castellanos, María Eugenia, Kakaire, Robert, Sekandi, Juliet N., Kiwanuka, Noah, Whalen, Christopher C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822548/
https://www.ncbi.nlm.nih.gov/pubmed/33481816
http://dx.doi.org/10.1371/journal.pone.0245328
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author Woldu, Henok G.
Zalwango, Sarah
Martinez, Leonardo
Castellanos, María Eugenia
Kakaire, Robert
Sekandi, Juliet N.
Kiwanuka, Noah
Whalen, Christopher C.
author_facet Woldu, Henok G.
Zalwango, Sarah
Martinez, Leonardo
Castellanos, María Eugenia
Kakaire, Robert
Sekandi, Juliet N.
Kiwanuka, Noah
Whalen, Christopher C.
author_sort Woldu, Henok G.
collection PubMed
description One principle of tuberculosis control is to prevent the development of tuberculosis disease by treating individuals with latent tuberculosis infection. The diagnosis of latent infection using the tuberculin skin test is not straightforward because of concerns about immunologic cross reactivity with the Bacille Calmette-Guerin (BCG) vaccine and environmental mycobacteria. To parse the effects of BCG vaccine and environmental mycobacteria on the tuberculin skin test, we estimated the frequency distribution of skin test results in two divisions of Kampala, Uganda, ten years apart. We then used mixture models to estimate parameters for underlying distributions and defined clinically meaningful criteria for latent infection, including an indeterminate category. Using percentiles of two underlying normal distributions, we defined two skin test readings to demarcate three ranges. Values of 10 mm or greater contained 90% of individuals with latent infection; values less than 7.2 mm contained 80% of individuals without infection. Contacts with values between 7.2 and 10 mm fell into an indeterminate zone where it was not possible to assign infection. We conclude that systematic tuberculin skin test surveys within populations at risk, combined with mixture model analysis, may be a reproducible, evidence-based approach to define meaningful criteria for latent tuberculosis infection.
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spelling pubmed-78225482021-02-01 Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda Woldu, Henok G. Zalwango, Sarah Martinez, Leonardo Castellanos, María Eugenia Kakaire, Robert Sekandi, Juliet N. Kiwanuka, Noah Whalen, Christopher C. PLoS One Research Article One principle of tuberculosis control is to prevent the development of tuberculosis disease by treating individuals with latent tuberculosis infection. The diagnosis of latent infection using the tuberculin skin test is not straightforward because of concerns about immunologic cross reactivity with the Bacille Calmette-Guerin (BCG) vaccine and environmental mycobacteria. To parse the effects of BCG vaccine and environmental mycobacteria on the tuberculin skin test, we estimated the frequency distribution of skin test results in two divisions of Kampala, Uganda, ten years apart. We then used mixture models to estimate parameters for underlying distributions and defined clinically meaningful criteria for latent infection, including an indeterminate category. Using percentiles of two underlying normal distributions, we defined two skin test readings to demarcate three ranges. Values of 10 mm or greater contained 90% of individuals with latent infection; values less than 7.2 mm contained 80% of individuals without infection. Contacts with values between 7.2 and 10 mm fell into an indeterminate zone where it was not possible to assign infection. We conclude that systematic tuberculin skin test surveys within populations at risk, combined with mixture model analysis, may be a reproducible, evidence-based approach to define meaningful criteria for latent tuberculosis infection. Public Library of Science 2021-01-22 /pmc/articles/PMC7822548/ /pubmed/33481816 http://dx.doi.org/10.1371/journal.pone.0245328 Text en © 2021 Woldu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Woldu, Henok G.
Zalwango, Sarah
Martinez, Leonardo
Castellanos, María Eugenia
Kakaire, Robert
Sekandi, Juliet N.
Kiwanuka, Noah
Whalen, Christopher C.
Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title_full Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title_fullStr Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title_full_unstemmed Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title_short Defining an intermediate category of tuberculin skin test: A mixture model analysis of two high-risk populations from Kampala, Uganda
title_sort defining an intermediate category of tuberculin skin test: a mixture model analysis of two high-risk populations from kampala, uganda
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822548/
https://www.ncbi.nlm.nih.gov/pubmed/33481816
http://dx.doi.org/10.1371/journal.pone.0245328
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