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.
Keywords: IPAF; IPF; Idiopathic pulmonary fibrosis; Interstitial lung disease; Interstitial pneumonia.