Abstract
Background Most phenotyping paradigms in sarcoidosis are based on expert opinion; however, no paradigm has been widely adopted because of the subjectivity in classification. We hypothesized that cluster analysis could be performed on common clinical variables to define more objective sarcoidosis phenotypes. MethodsModel-based clustering was performed using the VarSelLCM R package to identify distinct phenotypes of sarcoidosis based on 29 clinical features. The Integrated Completed Likelihood (ICL) criteria were used to estimate number of clusters. To identify features associated with cluster membership, features were ranked based on variable importance scores from the VarSelLCM model, and additional univariate tests (Fisher’s exact test and one-way ANOVA) were performed using q-values correcting for multiple testing. The Wasfi severity score was also compared between clusters. ResultsCluster analysis resulted in 6 sarcoidosis phenotypes. Salient characteristics for each cluster are as follows: Phenotype 1) supranormal lung function and majority Scadding stage 2/3; phenotype 2) supranormal lung function and majority Scadding stage 0/1; phenotype 3) normal lung function and split Scadding stages between 0/1 and 2/3; phenotype 4) obstructive lung function and majority Scadding stage 2/3; phenotype 5) restrictive lung function and majority Scadding stage 2/3; phenotype 6) mixed obstructive and restrictive lung function and mostly Scadding stage 4. Clusters 4,5,6 were significantly more likely to have ever been on immunosuppressive treatment and had higher Wasfi disease severity scores. ConclusionsCluster analysis produced 6 sarcoidosis phenotypes that demonstrated non-severe and severe phenotypes. Phenotypes 1,2,3 have less lung function abnormalities, a lower percentage on immunosuppressive treatment and lower Wasfi severity scores. Phenotypes 4,5,6 were characterized by lung function abnormalities, more parenchymal abnormalities, an increased percentage on immunosuppressive treatment and higher Wasfi severity scores. These data support using cluster analysis as an objective and clinically useful way to phenotype sarcoidosis subjects.