Evaluation of tuberculosis diagnostic test accuracy using Bayesian latent class analysis in the presence of conditional dependence between the diagnostic tests used in a community-based tuberculosis screening study.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 20 12 2022
accepted: 15 01 2023
entrez: 2 3 2023
pubmed: 3 3 2023
medline: 7 3 2023
Statut: epublish

Résumé

Diagnostic accuracy studies in pulmonary tuberculosis (PTB) are complicated by the lack of a perfect reference standard. This limitation can be handled using latent class analysis (LCA), assuming independence between diagnostic test results conditional on the true unobserved PTB status. Test results could remain dependent, however, e.g. with diagnostic tests based on a similar biological basis. If ignored, this gives misleading inferences. Our secondary analysis of data collected during the first year (May 2018 -May 2019) of a community-based multi-morbidity screening program conducted in the rural uMkhanyakude district of KwaZulu Natal, South Africa, used Bayesian LCA. Residents of the catchment area, aged ≥15 years and eligible for microbiological testing, were analyzed. Probit regression methods for dependent binary data sequentially regressed each binary test outcome on other observed test results, measured covariates and the true unobserved PTB status. Unknown model parameters were assigned Gaussian priors to evaluate overall PTB prevalence and diagnostic accuracy of 6 tests used to screen for PTB: any TB symptom, radiologist conclusion, Computer Aided Detection for TB version 5 (CAD4TBv5≥53), CAD4TBv6≥53, Xpert Ultra (excluding trace) and culture. Before the application of our proposed model, we evaluated its performance using a previously published childhood pulmonary TB (CPTB) dataset. Standard LCA assuming conditional independence yielded an unrealistic prevalence estimate of 18.6% which was not resolved by accounting for conditional dependence among the true PTB cases only. Allowing, also, for conditional dependence among the true non-PTB cases produced a 1.1% plausible prevalence. After incorporating age, sex, and HIV status in the analysis, we obtained 0.9% (95% CrI: 0.6, 1.3) overall prevalence. Males had higher PTB prevalence compared to females (1.2% vs. 0.8%). Similarly, HIV+ had a higher PTB prevalence compared to HIV- (1.3% vs. 0.8%). The overall sensitivity for Xpert Ultra (excluding trace) and culture were 62.2% (95% CrI: 48.7, 74.4) and 75.9% (95% CrI: 61.9, 89.2), respectively. Any chest X-ray abnormality, CAD4TBv5≥53 and CAD4TBv6≥53 had similar overall sensitivity. Up to 73.3% (95% CrI: 61.4, 83.4) of all true PTB cases did not report TB symptoms. Our flexible modelling approach yields plausible, easy-to-interpret estimates of sensitivity, specificity and PTB prevalence under more realistic assumptions. Failure to fully account for diagnostic test dependence can yield misleading inferences.

Identifiants

pubmed: 36862729
doi: 10.1371/journal.pone.0282417
pii: PONE-D-22-34380
pmc: PMC9980779
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0282417

Informations de copyright

Copyright: © 2023 Keter 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.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Alfred Kipyegon Keter (AK)

Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Antwerp, Belgium.
Centre for Community Based Research, Human Sciences Research Council, Pietermaritzburg, South Africa.
Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.

Lutgarde Lynen (L)

Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Antwerp, Belgium.

Alastair Van Heerden (A)

Centre for Community Based Research, Human Sciences Research Council, Pietermaritzburg, South Africa.
MRC/WITS Developmental Pathways for Health Research Unit, Department of Paediatrics, Faculty of Health Science, University of the Witwatersrand, Johannesburg, South Africa.

Emily Wong (E)

Africa Health Research Institute, Durban, South Africa.
Division of Infectious Diseases, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States of America.

Klaus Reither (K)

Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
University of Basel, Basel, Switzerland.

Els Goetghebeur (E)

Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.

Bart K M Jacobs (BKM)

Department of Clinical Sciences, Institute of Tropical Medicine Antwerp, Antwerp, Belgium.

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