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Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting
Background: Given the lack of a gold standard for latent tuberculosis infection (LTBI) and paucity of performance data from endemic settings, we compared test performance of the tuberculin skin test (TST) and two interferon-gamma-release assays (IGRAs) among health-care workers (HCWs) using latent c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720895/ https://www.ncbi.nlm.nih.gov/pubmed/31416206 http://dx.doi.org/10.3390/ijerph16162912 |
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author | Adams, Shahieda Ehrlich, Rodney Baatjies, Roslynn Dendukuri, Nandini Wang, Zhuoyu Dheda, Keertan |
author_facet | Adams, Shahieda Ehrlich, Rodney Baatjies, Roslynn Dendukuri, Nandini Wang, Zhuoyu Dheda, Keertan |
author_sort | Adams, Shahieda |
collection | PubMed |
description | Background: Given the lack of a gold standard for latent tuberculosis infection (LTBI) and paucity of performance data from endemic settings, we compared test performance of the tuberculin skin test (TST) and two interferon-gamma-release assays (IGRAs) among health-care workers (HCWs) using latent class analysis. The study was conducted in Cape Town, South Africa, a tuberculosis and human immunodeficiency virus (HIV) endemic setting Methods: 505 HCWs were screened for LTBI using TST, QuantiFERON-gold-in-tube (QFT-GIT) and T-SPOT.TB. A latent class model utilizing prior information on test characteristics was used to estimate test performance. Results: LTBI prevalence (95% credible interval) was 81% (71–88%). TST (10 mm cut-point) had highest sensitivity (93% (90–96%)) but lowest specificity (57%, (43–71%)). QFT-GIT sensitivity was 80% (74–91%) and specificity 96% (94–98%), and for TSPOT.TB, 74% (67–84%) and 96% (89–99%) respectively. Positive predictive values were high for IGRAs (90%) and TST (99%). All tests displayed low negative predictive values (range 47–66%). A composite rule using both TST and QFT-GIT greatly improved negative predictive value to 90% (range 80–97%). Conclusion: In an endemic setting a positive TST or IGRA was highly predictive of LTBI, while a combination of TST and IGRA had high rule-out value. These data inform the utility of LTBI-related immunodiagnostic tests in TB and HIV endemic settings. |
format | Online Article Text |
id | pubmed-6720895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67208952019-09-10 Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting Adams, Shahieda Ehrlich, Rodney Baatjies, Roslynn Dendukuri, Nandini Wang, Zhuoyu Dheda, Keertan Int J Environ Res Public Health Article Background: Given the lack of a gold standard for latent tuberculosis infection (LTBI) and paucity of performance data from endemic settings, we compared test performance of the tuberculin skin test (TST) and two interferon-gamma-release assays (IGRAs) among health-care workers (HCWs) using latent class analysis. The study was conducted in Cape Town, South Africa, a tuberculosis and human immunodeficiency virus (HIV) endemic setting Methods: 505 HCWs were screened for LTBI using TST, QuantiFERON-gold-in-tube (QFT-GIT) and T-SPOT.TB. A latent class model utilizing prior information on test characteristics was used to estimate test performance. Results: LTBI prevalence (95% credible interval) was 81% (71–88%). TST (10 mm cut-point) had highest sensitivity (93% (90–96%)) but lowest specificity (57%, (43–71%)). QFT-GIT sensitivity was 80% (74–91%) and specificity 96% (94–98%), and for TSPOT.TB, 74% (67–84%) and 96% (89–99%) respectively. Positive predictive values were high for IGRAs (90%) and TST (99%). All tests displayed low negative predictive values (range 47–66%). A composite rule using both TST and QFT-GIT greatly improved negative predictive value to 90% (range 80–97%). Conclusion: In an endemic setting a positive TST or IGRA was highly predictive of LTBI, while a combination of TST and IGRA had high rule-out value. These data inform the utility of LTBI-related immunodiagnostic tests in TB and HIV endemic settings. MDPI 2019-08-14 2019-08 /pmc/articles/PMC6720895/ /pubmed/31416206 http://dx.doi.org/10.3390/ijerph16162912 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Adams, Shahieda Ehrlich, Rodney Baatjies, Roslynn Dendukuri, Nandini Wang, Zhuoyu Dheda, Keertan Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title | Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title_full | Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title_fullStr | Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title_full_unstemmed | Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title_short | Evaluating Latent Tuberculosis Infection Test Performance Using Latent Class Analysis in a TB and HIV Endemic Setting |
title_sort | evaluating latent tuberculosis infection test performance using latent class analysis in a tb and hiv endemic setting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720895/ https://www.ncbi.nlm.nih.gov/pubmed/31416206 http://dx.doi.org/10.3390/ijerph16162912 |
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