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A simple prediction tool for inhaled corticosteroid response in asthmatic children

BACKGROUND: Inhaled corticosteroids are recommended as the first-line controller medication for childhood asthma owing to their multiple clinical benefits. However, heterogeneity in the response towards these drugs remains a significant clinical problem. METHODS: Children aged 5 to 18 years with mil...

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Autores principales: Wu, Yi-Fan, Su, Ming-Wei, Chiang, Bor-Luen, Yang, Yao-Hsu, Tsai, Ching-Hui, Lee, Yungling L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5721661/
https://www.ncbi.nlm.nih.gov/pubmed/29216859
http://dx.doi.org/10.1186/s12890-017-0533-0
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author Wu, Yi-Fan
Su, Ming-Wei
Chiang, Bor-Luen
Yang, Yao-Hsu
Tsai, Ching-Hui
Lee, Yungling L.
author_facet Wu, Yi-Fan
Su, Ming-Wei
Chiang, Bor-Luen
Yang, Yao-Hsu
Tsai, Ching-Hui
Lee, Yungling L.
author_sort Wu, Yi-Fan
collection PubMed
description BACKGROUND: Inhaled corticosteroids are recommended as the first-line controller medication for childhood asthma owing to their multiple clinical benefits. However, heterogeneity in the response towards these drugs remains a significant clinical problem. METHODS: Children aged 5 to 18 years with mild to moderate persistent asthma were recruited into the Taiwanese Consortium of Childhood Asthma Study. Their responses to inhaled corticosteroids were assessed based on their improvements in the asthma control test and peak expiratory flow. The predictors of responsiveness were demographic and clinical features that were available in primary care settings. We have developed a prediction model using logistic regression and have simplified it to formulate a practical tool. We assessed its predictive performance using the area under the receiver operating characteristic curve. RESULTS: Of the 73 asthmatic children with baseline and follow-up outcome measurements for inhaled corticosteroids treatment, 24 (33%) were defined as non-responders. The tool we have developed consisted of three predictors yielding a total score between 0 and 5, which are comprised of the following parameters: the age at physician-diagnosis of asthma, sex, and exhaled nitric oxide. Sensitivity and specificity of the tool for prediction of inhaled corticosteroids non-responsiveness, for a score of 3, were 0.75 and 0.69, respectively. The areas under the receiver operating characteristic curve for the prediction tool was 0.763. CONCLUSIONS: Our prediction tool represents a simple and low-cost method for predicting the response of inhaled corticosteroids treatment in asthmatic children.
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spelling pubmed-57216612017-12-12 A simple prediction tool for inhaled corticosteroid response in asthmatic children Wu, Yi-Fan Su, Ming-Wei Chiang, Bor-Luen Yang, Yao-Hsu Tsai, Ching-Hui Lee, Yungling L. BMC Pulm Med Research Article BACKGROUND: Inhaled corticosteroids are recommended as the first-line controller medication for childhood asthma owing to their multiple clinical benefits. However, heterogeneity in the response towards these drugs remains a significant clinical problem. METHODS: Children aged 5 to 18 years with mild to moderate persistent asthma were recruited into the Taiwanese Consortium of Childhood Asthma Study. Their responses to inhaled corticosteroids were assessed based on their improvements in the asthma control test and peak expiratory flow. The predictors of responsiveness were demographic and clinical features that were available in primary care settings. We have developed a prediction model using logistic regression and have simplified it to formulate a practical tool. We assessed its predictive performance using the area under the receiver operating characteristic curve. RESULTS: Of the 73 asthmatic children with baseline and follow-up outcome measurements for inhaled corticosteroids treatment, 24 (33%) were defined as non-responders. The tool we have developed consisted of three predictors yielding a total score between 0 and 5, which are comprised of the following parameters: the age at physician-diagnosis of asthma, sex, and exhaled nitric oxide. Sensitivity and specificity of the tool for prediction of inhaled corticosteroids non-responsiveness, for a score of 3, were 0.75 and 0.69, respectively. The areas under the receiver operating characteristic curve for the prediction tool was 0.763. CONCLUSIONS: Our prediction tool represents a simple and low-cost method for predicting the response of inhaled corticosteroids treatment in asthmatic children. BioMed Central 2017-12-07 /pmc/articles/PMC5721661/ /pubmed/29216859 http://dx.doi.org/10.1186/s12890-017-0533-0 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Wu, Yi-Fan
Su, Ming-Wei
Chiang, Bor-Luen
Yang, Yao-Hsu
Tsai, Ching-Hui
Lee, Yungling L.
A simple prediction tool for inhaled corticosteroid response in asthmatic children
title A simple prediction tool for inhaled corticosteroid response in asthmatic children
title_full A simple prediction tool for inhaled corticosteroid response in asthmatic children
title_fullStr A simple prediction tool for inhaled corticosteroid response in asthmatic children
title_full_unstemmed A simple prediction tool for inhaled corticosteroid response in asthmatic children
title_short A simple prediction tool for inhaled corticosteroid response in asthmatic children
title_sort simple prediction tool for inhaled corticosteroid response in asthmatic children
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5721661/
https://www.ncbi.nlm.nih.gov/pubmed/29216859
http://dx.doi.org/10.1186/s12890-017-0533-0
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