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Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival

BACKGROUND: The precise classification of idiopathic interstitial pneumonia (IIP) is essential for selecting treatment as well as estimating clinical outcomes; however, this is sometimes difficult in clinical practice. Therefore, cluster analysis was used to identify the clinical phenotypes of IIPs,...

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Autores principales: Aoshima, Yoichiro, Karayama, Masato, Horiike, Yasuoki, Mori, Kazutaka, Yasui, Hideki, Hozumi, Hironao, Suzuki, Yuzo, Furuhashi, Kazuki, Fujisawa, Tomoyuki, Enomoto, Noriyuki, Nakamura, Yutaro, Inui, Naoki, Suda, Takafumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7898746/
https://www.ncbi.nlm.nih.gov/pubmed/33618682
http://dx.doi.org/10.1186/s12890-021-01428-3
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author Aoshima, Yoichiro
Karayama, Masato
Horiike, Yasuoki
Mori, Kazutaka
Yasui, Hideki
Hozumi, Hironao
Suzuki, Yuzo
Furuhashi, Kazuki
Fujisawa, Tomoyuki
Enomoto, Noriyuki
Nakamura, Yutaro
Inui, Naoki
Suda, Takafumi
author_facet Aoshima, Yoichiro
Karayama, Masato
Horiike, Yasuoki
Mori, Kazutaka
Yasui, Hideki
Hozumi, Hironao
Suzuki, Yuzo
Furuhashi, Kazuki
Fujisawa, Tomoyuki
Enomoto, Noriyuki
Nakamura, Yutaro
Inui, Naoki
Suda, Takafumi
author_sort Aoshima, Yoichiro
collection PubMed
description BACKGROUND: The precise classification of idiopathic interstitial pneumonia (IIP) is essential for selecting treatment as well as estimating clinical outcomes; however, this is sometimes difficult in clinical practice. Therefore, cluster analysis was used to identify the clinical phenotypes of IIPs, and its usefulness for predicting clinical outcomes was evaluated. METHODS: Cluster analysis was performed using clinical features including patients’ demographics; histories; pulmonary function test data; and laboratory, physical and radiological findings. RESULTS: In 337 patients with IIPs, four clusters were identified: Cluster I, in which > 80% of the patients had autoimmune features; Cluster II, which had the lowest rate of smoking, the lowest percent predicted forced vital capacity (%FVC) and the lowest body mass index (BMI); Cluster III, which had the highest rate of smoking, the highest rate of dust exposure, the second lowest %FVC and normal BMI; and Cluster IV, which exhibited maintenance of %FVC and normal BMI. Cluster IV had significantly longer overall survival than Clusters II and III. Clusters I and III had significantly longer overall survival than Cluster II. Clusters II and III had a significantly higher cumulative incidence of acute exacerbation than Cluster IV. CONCLUSION: Cluster analysis using clinical features identified four clinical phenotypes of IIPs, which may be useful for predicting the risk of acute exacerbation and overall survival.
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spelling pubmed-78987462021-02-23 Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival Aoshima, Yoichiro Karayama, Masato Horiike, Yasuoki Mori, Kazutaka Yasui, Hideki Hozumi, Hironao Suzuki, Yuzo Furuhashi, Kazuki Fujisawa, Tomoyuki Enomoto, Noriyuki Nakamura, Yutaro Inui, Naoki Suda, Takafumi BMC Pulm Med Research Article BACKGROUND: The precise classification of idiopathic interstitial pneumonia (IIP) is essential for selecting treatment as well as estimating clinical outcomes; however, this is sometimes difficult in clinical practice. Therefore, cluster analysis was used to identify the clinical phenotypes of IIPs, and its usefulness for predicting clinical outcomes was evaluated. METHODS: Cluster analysis was performed using clinical features including patients’ demographics; histories; pulmonary function test data; and laboratory, physical and radiological findings. RESULTS: In 337 patients with IIPs, four clusters were identified: Cluster I, in which > 80% of the patients had autoimmune features; Cluster II, which had the lowest rate of smoking, the lowest percent predicted forced vital capacity (%FVC) and the lowest body mass index (BMI); Cluster III, which had the highest rate of smoking, the highest rate of dust exposure, the second lowest %FVC and normal BMI; and Cluster IV, which exhibited maintenance of %FVC and normal BMI. Cluster IV had significantly longer overall survival than Clusters II and III. Clusters I and III had significantly longer overall survival than Cluster II. Clusters II and III had a significantly higher cumulative incidence of acute exacerbation than Cluster IV. CONCLUSION: Cluster analysis using clinical features identified four clinical phenotypes of IIPs, which may be useful for predicting the risk of acute exacerbation and overall survival. BioMed Central 2021-02-22 /pmc/articles/PMC7898746/ /pubmed/33618682 http://dx.doi.org/10.1186/s12890-021-01428-3 Text en © The Author(s) 2021 Open AccessThis 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/. 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 in a credit line to the data.
spellingShingle Research Article
Aoshima, Yoichiro
Karayama, Masato
Horiike, Yasuoki
Mori, Kazutaka
Yasui, Hideki
Hozumi, Hironao
Suzuki, Yuzo
Furuhashi, Kazuki
Fujisawa, Tomoyuki
Enomoto, Noriyuki
Nakamura, Yutaro
Inui, Naoki
Suda, Takafumi
Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title_full Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title_fullStr Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title_full_unstemmed Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title_short Cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
title_sort cluster analysis-based clinical phenotypes of idiopathic interstitial pneumonias: associations with acute exacerbation and overall survival
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7898746/
https://www.ncbi.nlm.nih.gov/pubmed/33618682
http://dx.doi.org/10.1186/s12890-021-01428-3
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