ArticleRespiratory research2022
Clinical phenotyping in sarcoidosis using cluster analysis.
Article in Respiratory research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 22 citations in OpenAlex.
- New Therapies for Sarcoidosis: Molecular and Pathophysiological Basis.International journal of molecular sciences · 2026Review
- Radiomic profiling of chest CT in a cohort of sarcoidosis cases.Scientific reports · 2026Article
- Expert intuition vs. Algorithmic clustering: Mapping radiological subtypes in pulmonary sarcoidosis.PloS one · 2026Article
- Occupational exposures in sarcoidosis: a protocol for a multicentre regional case-control study in the UK.BMJ open respiratory research · 2025Article
- Extracellular vesicles in sarcoidosis: unlocking molecular signatures for precision therapy.ERJ open research · 2025Article
- The textures of sarcoidosis: quantifying lung disease through variograms.Physics in medicine and biology · 2025Article
- The Frequency of Mediastinal Lymph Node Calcification in Sarcoidosis Patients and the Influencing Factors.Medicina (Kaunas, Lithuania) · 2024Article
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- Big data in sarcoidosis.Current opinion in pulmonary medicine · 2024Review
- The textures of sarcoidosis: quantifying lung disease through variograms.medRxiv : the preprint server for health sciences · 2024Article
- Comparison of organ involvement clusters in Black and White American sarcoidosis patients from a prospectively collected patient registry.Respiratory medicine · 2024Article
- Cluster features in fibrosing interstitial lung disease and associations with prognosis.BMC pulmonary medicine · 2023Article
- Pulmonary Function in Pulmonary Sarcoidosis.Journal of clinical medicine · 2023Review
- Is this the Dawning of AI for Sarcoidosis?Lung · 2023Article
- Biomarkers and molecular endotypes of sarcoidosis: lessons from omics and non-omics studies.Frontiers in immunology · 2023Review
- From Karl Wurm and Guy Scadding's staging toFrontiers in medicine · 2023Article
- Decoding sarcoidosis chronicity through phenotypic profiling.Therapeutic advances in respiratory diseaseArticle
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundMost 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.
methodsWe 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.
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. 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.
conclusionsCluster 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.
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