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Cluster features in fibrosing interstitial lung disease and associations with prognosis

BACKGROUND: Clustering is helpful in identifying subtypes in complex fibrosing interstitial lung disease (F-ILD) and associating them with prognosis at an early stage of the disease to improve treatment management. We aimed to identify associations between clinical characteristics and outcomes in pa...

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Autores principales: Wang, Yuanying, Sun, Di, Wang, Jingwei, Yu, Shiwen, Wu, Na, Ye, Qiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621076/
https://www.ncbi.nlm.nih.gov/pubmed/37914987
http://dx.doi.org/10.1186/s12890-023-02735-7
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author Wang, Yuanying
Sun, Di
Wang, Jingwei
Yu, Shiwen
Wu, Na
Ye, Qiao
author_facet Wang, Yuanying
Sun, Di
Wang, Jingwei
Yu, Shiwen
Wu, Na
Ye, Qiao
author_sort Wang, Yuanying
collection PubMed
description BACKGROUND: Clustering is helpful in identifying subtypes in complex fibrosing interstitial lung disease (F-ILD) and associating them with prognosis at an early stage of the disease to improve treatment management. We aimed to identify associations between clinical characteristics and outcomes in patients with F-ILD. METHODS: Retrospectively, 575 out of 926 patients with F-ILD were eligible for analysis. Four clusters were identified based on baseline data using cluster analysis. The clinical characteristics and outcomes were compared among the groups. RESULTS: Cluster 1 was characterized by a high prevalence of comorbidities and hypoxemia at rest, with the worst lung function at baseline; Cluster 2 by young female patients with less or no smoking history; Cluster 3 by male patients with highest smoking history, the most noticeable signs of velcro crackles and clubbing of fingers, and the severe lung involvement on chest image; Cluster 4 by male patients with a high percentage of occupational or environmental exposure. Clusters 1 (median overall survival [OS] = 7.0 years) and 3 (OS = 5.9 years) had shorter OS than Clusters 2 (OS = not reached, Cluster 1: p < 0.001, Cluster 3: p < 0.001) and 4 (OS = not reached, Cluster 1: p = 0.004, Cluster 3: p < 0.001). Clusters 1 and 3 had a higher cumulative incidence of acute exacerbation than Clusters 2 (Cluster 1: p < 0.001, Cluster 3: p = 0.014) and 4 (Cluster 1: p < 0.001, Cluster 3: p = 0.006). Stratification by using clusters also independently predicted acute exacerbation (p < 0.001) and overall survival (p < 0.001). CONCLUSIONS: The high degree of disease heterogeneity of F-ILD can be underscored by four clusters based on clinical characteristics, which may be helpful in predicting the risk of fibrosis progression, acute exacerbation and overall survival. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02735-7.
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spelling pubmed-106210762023-11-03 Cluster features in fibrosing interstitial lung disease and associations with prognosis Wang, Yuanying Sun, Di Wang, Jingwei Yu, Shiwen Wu, Na Ye, Qiao BMC Pulm Med Research BACKGROUND: Clustering is helpful in identifying subtypes in complex fibrosing interstitial lung disease (F-ILD) and associating them with prognosis at an early stage of the disease to improve treatment management. We aimed to identify associations between clinical characteristics and outcomes in patients with F-ILD. METHODS: Retrospectively, 575 out of 926 patients with F-ILD were eligible for analysis. Four clusters were identified based on baseline data using cluster analysis. The clinical characteristics and outcomes were compared among the groups. RESULTS: Cluster 1 was characterized by a high prevalence of comorbidities and hypoxemia at rest, with the worst lung function at baseline; Cluster 2 by young female patients with less or no smoking history; Cluster 3 by male patients with highest smoking history, the most noticeable signs of velcro crackles and clubbing of fingers, and the severe lung involvement on chest image; Cluster 4 by male patients with a high percentage of occupational or environmental exposure. Clusters 1 (median overall survival [OS] = 7.0 years) and 3 (OS = 5.9 years) had shorter OS than Clusters 2 (OS = not reached, Cluster 1: p < 0.001, Cluster 3: p < 0.001) and 4 (OS = not reached, Cluster 1: p = 0.004, Cluster 3: p < 0.001). Clusters 1 and 3 had a higher cumulative incidence of acute exacerbation than Clusters 2 (Cluster 1: p < 0.001, Cluster 3: p = 0.014) and 4 (Cluster 1: p < 0.001, Cluster 3: p = 0.006). Stratification by using clusters also independently predicted acute exacerbation (p < 0.001) and overall survival (p < 0.001). CONCLUSIONS: The high degree of disease heterogeneity of F-ILD can be underscored by four clusters based on clinical characteristics, which may be helpful in predicting the risk of fibrosis progression, acute exacerbation and overall survival. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-023-02735-7. BioMed Central 2023-11-01 /pmc/articles/PMC10621076/ /pubmed/37914987 http://dx.doi.org/10.1186/s12890-023-02735-7 Text en © The Author(s) 2023 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
Wang, Yuanying
Sun, Di
Wang, Jingwei
Yu, Shiwen
Wu, Na
Ye, Qiao
Cluster features in fibrosing interstitial lung disease and associations with prognosis
title Cluster features in fibrosing interstitial lung disease and associations with prognosis
title_full Cluster features in fibrosing interstitial lung disease and associations with prognosis
title_fullStr Cluster features in fibrosing interstitial lung disease and associations with prognosis
title_full_unstemmed Cluster features in fibrosing interstitial lung disease and associations with prognosis
title_short Cluster features in fibrosing interstitial lung disease and associations with prognosis
title_sort cluster features in fibrosing interstitial lung disease and associations with prognosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10621076/
https://www.ncbi.nlm.nih.gov/pubmed/37914987
http://dx.doi.org/10.1186/s12890-023-02735-7
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