Clinical phenotyping in sarcoidosis using cluster analysis

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.

Methods: We performed a retrospective cohort study of 554 sarcoidosis cases to identify distinct phenotypes of sarcoidosis based on 29 clinical features. Model-based clustering was performed using the VarSelLCM R package and 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.

Results: Cluster 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. Although there were differences in the percentages, all Scadding stages were encompassed by all of the phenotypes, except for phenotype 1, in which none were 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.

Conclusions: Cluster analysis produced 6 sarcoidosis phenotypes that demonstrated less 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 and to empower clinicians to identify those with more severe disease versus those who have less severe disease, independent of Scadding stage.

Keywords: Cluster analysis; Disease severity; Phenotypes; Pulmonary; Sarcoidosis.

Fig. 1

Comparison of lung function parameters among clusters. For each cluster, median and IQR are shown by boxplots and means are shown by x in the center of boxplots for a FEV1pp b FVCpp and c FEV1/FVC. Potential outliers are indicated by distinct points

Fig. 2

Distribution of Scadding stages 0–4 in each cluster. The representation of each Scadding stage in a cluster by percent is shown for all six clusters

Fig. 3

Comparison of duration of disease in years among clusters. For each cluster, median and IQR are shown by boxplots and means are shown by x in the center of boxplots. Potential outliers are indicated by distinct points

Fig. 4

Distribution of cases treated with non-corticosteroid immunosuppression in each cluster. Percent of individuals who ever received immunosuppressive treatment are represented in dark gray, while percent of individual who have never received immunosuppressive treatment are in light gray

Fig. 5

Wasfi Scores by Cluster. For each cluster, median and IQR are shown by boxplots and means are shown by x in the center of boxplots. Higher scores indicate greater severity

Fig. 6

a Cluster Descriptions by Less Severe Disease Features. b Cluster Descriptions by More Severe Disease Features. The first column describes the cluster number, and the second column describes the cluster name. The third column includes significant differences in the six most important variables for clustering; arrows indicate a significant difference between less severe clusters (1, 2, 3) and more severe clusters (4, 5, 6) (q < 0.05). The fourth column shows which severe disease features are present in clusters; shading in the Venn diagram indicates that the majority of individuals had that particular disease feature; partial shading indicates half of individuals had the disease feature. The fifth column describes significant pairwise differences between clusters (q < 0.05). Finally, the sixth column describes the mean Wasfi score for that cluster