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, and Whalen, Christopher C. (2021) Defining an intermediate category of tuberculin skin test: a mixture model analysis of two high-risk populations from Kampala, Uganda. PLoS ONE, 16 (1). e0245328.

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Abstract

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.

Item ID: 68019
Item Type: Article (Research - C1)
ISSN: 1932-6203
Keywords: Mycobacterium tuberculosis; mixture model; tuberculin skin test
Copyright Information: © 2021 Woldu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funders: National Institute of Allergy and Infectious Disease (NIAID), Schlumberger Foundation (SF)
Projects and Grants: NIAID R01 AI093856, NIAID NO1-AI95383, NIAID D43- TW01004, SF Faculty for the Future Fellowship
Date Deposited: 17 Jun 2021 01:15
FoR Codes: 42 HEALTH SCIENCES > 4202 Epidemiology > 420207 Major global burdens of disease @ 50%
42 HEALTH SCIENCES > 4206 Public health > 420699 Public health not elsewhere classified @ 50%
SEO Codes: 20 HEALTH > 2004 Public health (excl. specific population health) > 200404 Disease distribution and transmission (incl. surveillance and response) @ 100%
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