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Concordance rate of a four-quadrant plot for repeated measurements

BACKGROUND: To assure the equivalence between new clinical measurement methods and the standard methods, the four-quadrant plot and the plot’s concordance rate is used in clinical practice, along with Bland-Altman analysis. The conventional concordance rate does not consider the correlation among th...

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Autores principales: Hiraishi, Mayu, Tanioka, Kensuke, Shimokawa, Toshio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638183/
https://www.ncbi.nlm.nih.gov/pubmed/34852772
http://dx.doi.org/10.1186/s12874-021-01461-0
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author Hiraishi, Mayu
Tanioka, Kensuke
Shimokawa, Toshio
author_facet Hiraishi, Mayu
Tanioka, Kensuke
Shimokawa, Toshio
author_sort Hiraishi, Mayu
collection PubMed
description BACKGROUND: To assure the equivalence between new clinical measurement methods and the standard methods, the four-quadrant plot and the plot’s concordance rate is used in clinical practice, along with Bland-Altman analysis. The conventional concordance rate does not consider the correlation among the data on individual subjects, which may affect its proper evaluation. METHODS: We propose a new concordance rate for the four-quadrant plot based on multivariate normal distribution to take into account the covariance within each individual subject. The proposed concordance rate is formulated as the conditional probability of the agreement. It contains a parameter to set the minimum concordant number between two measurement methods, which is regarded as agreement. This parameter allows flexibility in the interpretation of the results. RESULTS: Through numerical simulations, the AUC value of the proposed method was 0.967, while that of the conventional concordance rate was 0.938. In the application to a real example, the AUC value of the proposed method was 0.999 and that of the conventional concordance rate was 0.964. CONCLUSION: From the results of numerical simulations and a real example, the proposed concordance rate showed better accuracy and higher diagnosability than the conventional approaches.
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spelling pubmed-86381832021-12-02 Concordance rate of a four-quadrant plot for repeated measurements Hiraishi, Mayu Tanioka, Kensuke Shimokawa, Toshio BMC Med Res Methodol Research BACKGROUND: To assure the equivalence between new clinical measurement methods and the standard methods, the four-quadrant plot and the plot’s concordance rate is used in clinical practice, along with Bland-Altman analysis. The conventional concordance rate does not consider the correlation among the data on individual subjects, which may affect its proper evaluation. METHODS: We propose a new concordance rate for the four-quadrant plot based on multivariate normal distribution to take into account the covariance within each individual subject. The proposed concordance rate is formulated as the conditional probability of the agreement. It contains a parameter to set the minimum concordant number between two measurement methods, which is regarded as agreement. This parameter allows flexibility in the interpretation of the results. RESULTS: Through numerical simulations, the AUC value of the proposed method was 0.967, while that of the conventional concordance rate was 0.938. In the application to a real example, the AUC value of the proposed method was 0.999 and that of the conventional concordance rate was 0.964. CONCLUSION: From the results of numerical simulations and a real example, the proposed concordance rate showed better accuracy and higher diagnosability than the conventional approaches. BioMed Central 2021-12-01 /pmc/articles/PMC8638183/ /pubmed/34852772 http://dx.doi.org/10.1186/s12874-021-01461-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Hiraishi, Mayu
Tanioka, Kensuke
Shimokawa, Toshio
Concordance rate of a four-quadrant plot for repeated measurements
title Concordance rate of a four-quadrant plot for repeated measurements
title_full Concordance rate of a four-quadrant plot for repeated measurements
title_fullStr Concordance rate of a four-quadrant plot for repeated measurements
title_full_unstemmed Concordance rate of a four-quadrant plot for repeated measurements
title_short Concordance rate of a four-quadrant plot for repeated measurements
title_sort concordance rate of a four-quadrant plot for repeated measurements
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8638183/
https://www.ncbi.nlm.nih.gov/pubmed/34852772
http://dx.doi.org/10.1186/s12874-021-01461-0
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