Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Keter, Alfred Kipyegon, Lynen, Lutgarde, Van Heerden, Alastair, Wong, Emily, Reither, Klaus, Goetghebeur, Els, Jacobs, Bart K. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980779/
https://www.ncbi.nlm.nih.gov/pubmed/36862729
http://dx.doi.org/10.1371/journal.pone.0282417
_version_ 1784899962325172224
author Keter, Alfred Kipyegon
Lynen, Lutgarde
Van Heerden, Alastair
Wong, Emily
Reither, Klaus
Goetghebeur, Els
Jacobs, Bart K. M.
author_facet Keter, Alfred Kipyegon
Lynen, Lutgarde
Van Heerden, Alastair
Wong, Emily
Reither, Klaus
Goetghebeur, Els
Jacobs, Bart K. M.
author_sort Keter, Alfred Kipyegon
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9980779
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-99807792023-03-03 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 Keter, Alfred Kipyegon Lynen, Lutgarde Van Heerden, Alastair Wong, Emily Reither, Klaus Goetghebeur, Els Jacobs, Bart K. M. PLoS One Research Article 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. Public Library of Science 2023-03-02 /pmc/articles/PMC9980779/ /pubmed/36862729 http://dx.doi.org/10.1371/journal.pone.0282417 Text en © 2023 Keter et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Keter, Alfred Kipyegon
Lynen, Lutgarde
Van Heerden, Alastair
Wong, Emily
Reither, Klaus
Goetghebeur, Els
Jacobs, Bart K. M.
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980779/
https://www.ncbi.nlm.nih.gov/pubmed/36862729
http://dx.doi.org/10.1371/journal.pone.0282417
work_keys_str_mv AT keteralfredkipyegon evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT lynenlutgarde evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT vanheerdenalastair evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT wongemily evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT reitherklaus evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT goetghebeurels evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy
AT jacobsbartkm evaluationoftuberculosisdiagnostictestaccuracyusingbayesianlatentclassanalysisinthepresenceofconditionaldependencebetweenthediagnostictestsusedinacommunitybasedtuberculosisscreeningstudy