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
Abstract
Abstract
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.
Publisher
Springer Science and Business Media LLC
Subject
Pulmonary and Respiratory Medicine
Cited by
4 articles.
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