Cargando…

Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach

Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In...

Descripción completa

Detalles Bibliográficos
Autores principales: Picasso-Risso, Catalina, Perez, Andres, Gil, Andres, Nunez, Alvaro, Salaberry, Ximena, Suanes, Alejandra, Alvarez, Julio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701407/
https://www.ncbi.nlm.nih.gov/pubmed/31457019
http://dx.doi.org/10.3389/fvets.2019.00261
_version_ 1783445052169650176
author Picasso-Risso, Catalina
Perez, Andres
Gil, Andres
Nunez, Alvaro
Salaberry, Ximena
Suanes, Alejandra
Alvarez, Julio
author_facet Picasso-Risso, Catalina
Perez, Andres
Gil, Andres
Nunez, Alvaro
Salaberry, Ximena
Suanes, Alejandra
Alvarez, Julio
author_sort Picasso-Risso, Catalina
collection PubMed
description Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In this context, latent-class models implemented using a Bayesian approach can help to assess the accuracy of diagnostic tests incorporating previous knowledge on test performance and disease prevalence. In Uruguay, bTB-prevalence has increased in the past decades partially because of the limited accuracy of the diagnostic strategy in place, based on intradermal testing (caudal fold test, CFT, for screening and comparative cervical test, CCT, for confirmation) and slaughter of reactors. Here, we evaluated the performance of two alternative bTB-diagnostic tools, the interferon-gamma assay, IGRA, and the enzyme-linked immunosorbent assay (ELISA), which had never been used in Uruguay in the absence of a gold standard. In order to do so animals from two heavily infected dairy herds and tested with CFT-CCT were also analyzed with the IGRA using two antigens (study 1) and the ELISA (study 2). The accuracy of the IGRA and ELISA was assessed fitting two latent-class models: a two test-one population model (LCA-a) based on the analysis of CFT/CFT-CCT test results and one in-vitro test (IGRA/ELISA), and a one test-one population model (LCA-b) using the IGRA or ELISA information in which the prevalence was modeled using information from the skin tests. Posterior estimates for model LCA-a suggested that IGRA was as sensitive (75–78%) as the CFT and more sensitive than the serial use of CFT-CCT. Its specificity (90–96%) was superior to the one for the CFT and equivalent to the use of CFT-CCT. Estimates from LCA-b models consistently yielded lower posterior Se estimates for the IGRA but similar results for its Sp. Estimates for the Se (52% 95%PPI:44.41-71.28) and the Sp (92% 95%PPI:78.63–98.76) of the ELISA were however similar regardless of the model used. These results suggest that the incorporation of IGRA for detection of bTB in highly infected herds could be a useful tool to improve the sensitivity of the bTB-control in Uruguay.
format Online
Article
Text
id pubmed-6701407
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-67014072019-08-27 Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach Picasso-Risso, Catalina Perez, Andres Gil, Andres Nunez, Alvaro Salaberry, Ximena Suanes, Alejandra Alvarez, Julio Front Vet Sci Veterinary Science Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In this context, latent-class models implemented using a Bayesian approach can help to assess the accuracy of diagnostic tests incorporating previous knowledge on test performance and disease prevalence. In Uruguay, bTB-prevalence has increased in the past decades partially because of the limited accuracy of the diagnostic strategy in place, based on intradermal testing (caudal fold test, CFT, for screening and comparative cervical test, CCT, for confirmation) and slaughter of reactors. Here, we evaluated the performance of two alternative bTB-diagnostic tools, the interferon-gamma assay, IGRA, and the enzyme-linked immunosorbent assay (ELISA), which had never been used in Uruguay in the absence of a gold standard. In order to do so animals from two heavily infected dairy herds and tested with CFT-CCT were also analyzed with the IGRA using two antigens (study 1) and the ELISA (study 2). The accuracy of the IGRA and ELISA was assessed fitting two latent-class models: a two test-one population model (LCA-a) based on the analysis of CFT/CFT-CCT test results and one in-vitro test (IGRA/ELISA), and a one test-one population model (LCA-b) using the IGRA or ELISA information in which the prevalence was modeled using information from the skin tests. Posterior estimates for model LCA-a suggested that IGRA was as sensitive (75–78%) as the CFT and more sensitive than the serial use of CFT-CCT. Its specificity (90–96%) was superior to the one for the CFT and equivalent to the use of CFT-CCT. Estimates from LCA-b models consistently yielded lower posterior Se estimates for the IGRA but similar results for its Sp. Estimates for the Se (52% 95%PPI:44.41-71.28) and the Sp (92% 95%PPI:78.63–98.76) of the ELISA were however similar regardless of the model used. These results suggest that the incorporation of IGRA for detection of bTB in highly infected herds could be a useful tool to improve the sensitivity of the bTB-control in Uruguay. Frontiers Media S.A. 2019-08-13 /pmc/articles/PMC6701407/ /pubmed/31457019 http://dx.doi.org/10.3389/fvets.2019.00261 Text en Copyright © 2019 Picasso-Risso, Perez, Gil, Nunez, Salaberry, Suanes and Alvarez. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Veterinary Science
Picasso-Risso, Catalina
Perez, Andres
Gil, Andres
Nunez, Alvaro
Salaberry, Ximena
Suanes, Alejandra
Alvarez, Julio
Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title_full Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title_fullStr Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title_full_unstemmed Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title_short Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach
title_sort modeling the accuracy of two in-vitro bovine tuberculosis tests using a bayesian approach
topic Veterinary Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6701407/
https://www.ncbi.nlm.nih.gov/pubmed/31457019
http://dx.doi.org/10.3389/fvets.2019.00261
work_keys_str_mv AT picassorissocatalina modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT perezandres modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT gilandres modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT nunezalvaro modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT salaberryximena modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT suanesalejandra modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach
AT alvarezjulio modelingtheaccuracyoftwoinvitrobovinetuberculosistestsusingabayesianapproach