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An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests

Latent class analysis is a widely used statistical method for evaluating diagnostic tests without any gold standard. It requires the results of at least two tests applied to the same individuals. Based on the resulting response patterns, the method estimates the test accuracy and the unknown disease...

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Autores principales: Schoneberg, Clara, Böttcher, Jens, Janowetz, Britta, Rostalski, Anja, Kreienbrock, Lothar, Campe, Amely
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789123/
https://www.ncbi.nlm.nih.gov/pubmed/35077518
http://dx.doi.org/10.1371/journal.pone.0262944
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author Schoneberg, Clara
Böttcher, Jens
Janowetz, Britta
Rostalski, Anja
Kreienbrock, Lothar
Campe, Amely
author_facet Schoneberg, Clara
Böttcher, Jens
Janowetz, Britta
Rostalski, Anja
Kreienbrock, Lothar
Campe, Amely
author_sort Schoneberg, Clara
collection PubMed
description Latent class analysis is a widely used statistical method for evaluating diagnostic tests without any gold standard. It requires the results of at least two tests applied to the same individuals. Based on the resulting response patterns, the method estimates the test accuracy and the unknown disease status for all individuals in the sample. An important assumption is the conditional independence of the tests. If tests with the same biological principle are used, the assumption is not fulfilled, which may lead to biased results. In a recent publication, we developed a method that considers the dependencies in the latent class model and estimates all parameters using frequentist methods. Here, we evaluate the practicability of the method by applying it to the results of six ELISA tests for antibodies against the porcine reproductive and respiratory syndrome (PRRS) virus in pigs that generally follow the same biological principle. First, we present different methods of identifying suitable starting values for the algorithm and apply these to the dataset and a vaccinated subgroup. We present the calculated values of the test accuracies, the estimated proportion of antibody-positive animals and the dependency structure for both datasets. Different starting values led to matching results for the entire dataset. For the vaccinated subgroup, the results were more dependent on the selected starting values. All six ELISA tests are well suited to detect antibodies against PRRS virus, whereas none of the tests had the best values for sensitivity and specificity simultaneously. The results thus show that the method used is able to determine the parameter values of conditionally dependent tests with suitable starting values. The choice of test should be based on the general fit-for-purpose concept and the population under study.
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spelling pubmed-87891232022-01-26 An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests Schoneberg, Clara Böttcher, Jens Janowetz, Britta Rostalski, Anja Kreienbrock, Lothar Campe, Amely PLoS One Research Article Latent class analysis is a widely used statistical method for evaluating diagnostic tests without any gold standard. It requires the results of at least two tests applied to the same individuals. Based on the resulting response patterns, the method estimates the test accuracy and the unknown disease status for all individuals in the sample. An important assumption is the conditional independence of the tests. If tests with the same biological principle are used, the assumption is not fulfilled, which may lead to biased results. In a recent publication, we developed a method that considers the dependencies in the latent class model and estimates all parameters using frequentist methods. Here, we evaluate the practicability of the method by applying it to the results of six ELISA tests for antibodies against the porcine reproductive and respiratory syndrome (PRRS) virus in pigs that generally follow the same biological principle. First, we present different methods of identifying suitable starting values for the algorithm and apply these to the dataset and a vaccinated subgroup. We present the calculated values of the test accuracies, the estimated proportion of antibody-positive animals and the dependency structure for both datasets. Different starting values led to matching results for the entire dataset. For the vaccinated subgroup, the results were more dependent on the selected starting values. All six ELISA tests are well suited to detect antibodies against PRRS virus, whereas none of the tests had the best values for sensitivity and specificity simultaneously. The results thus show that the method used is able to determine the parameter values of conditionally dependent tests with suitable starting values. The choice of test should be based on the general fit-for-purpose concept and the population under study. Public Library of Science 2022-01-25 /pmc/articles/PMC8789123/ /pubmed/35077518 http://dx.doi.org/10.1371/journal.pone.0262944 Text en © 2022 Schoneberg 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
Schoneberg, Clara
Böttcher, Jens
Janowetz, Britta
Rostalski, Anja
Kreienbrock, Lothar
Campe, Amely
An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title_full An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title_fullStr An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title_full_unstemmed An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title_short An intercomparison study of ELISAs for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
title_sort intercomparison study of elisas for the detection of porcine reproductive and respiratory syndrome virus – evaluating six conditionally dependent tests
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789123/
https://www.ncbi.nlm.nih.gov/pubmed/35077518
http://dx.doi.org/10.1371/journal.pone.0262944
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