Journal article
Clinical phenotyping in sarcoidosis using cluster analysis
Respiratory research, Vol.23(1), pp.88-88
01/01/2022
DOI: 10.1186/s12931-022-01993-z
PMCID: PMC8994095
PMID: 35397561
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.
Details
- Title: Subtitle
- Clinical phenotyping in sarcoidosis using cluster analysis
- Creators
- Nancy W. Lin - University of Colorado DenverJaron Arbet - Colorado School of Public HealthMargaret M. Mroz - National Jewish HealthShu-Yi Liao - University of Colorado DenverClara I. Restrepo - University of Colorado DenverAnnyce S. Mayer - National Jewish HealthLi Li - University of Colorado DenverBriana Q. Barkes - National Jewish HealthSarah Schrock - Colorado School of Public HealthNabeel Hamzeh - University of IowaTasha E. Fingerlin - Colorado School of Public HealthNichole E. Carlson - Colorado School of Public HealthLisa A. Maier - University of Colorado Denver
- Resource Type
- Journal article
- Publication Details
- Respiratory research, Vol.23(1), pp.88-88
- DOI
- 10.1186/s12931-022-01993-z
- PMID
- 35397561
- PMCID
- PMC8994095
- NLM abbreviation
- Respir Res
- ISSN
- 1465-9921
- eISSN
- 1465-993X
- Publisher
- BioMed Central
- Grant note
- 1R01 HL142049-03; 5R01HL114587-06 / ;
- Language
- English
- Date published
- 01/01/2022
- Academic Unit
- Pulmonary, Critical Care, and Occupational Medicine; Internal Medicine
- Record Identifier
- 9984359819502771
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