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Decoding sarcoidosis chronicity through phenotypic profiling
Ioannis Tomos1, Georgia Vourli2, Andreas M Matthaiou3
15th Pulmonary Medicine Department, SOTIRIA Chest Diseases Hospital of Athens, Athens 11527, Greece.
Therapeutic Advances in Respiratory Disease
|June 27, 2026
Summary
This study identified two distinct sarcoidosis phenotypes using cluster analysis. Arthritis presence strongly predicts chronicity, while lymphadenopathy may be protective against chronic sarcoidosis.
Area of Science:
- Pulmonary Medicine
- Immunology
- Genetics
Background:
- Sarcoidosis is a granulomatous disease with unpredictable clinical behavior, lacking predictive phenotyping for chronicity.
- Current clinical practice lacks reliable strategies to identify patients progressing to chronic sarcoidosis.
Purpose of the Study:
- To identify distinct sarcoidosis phenotypic clusters based on clinical characteristics.
- To evaluate the predictive value of these clusters for disease outcomes, specifically chronicity.
Main Methods:
- Retrospective, single-center study of 68 histologically confirmed sarcoidosis patients with >2 years follow-up.
- Utilized Multiple Correspondence Analysis (MCA) and Hierarchical Clustering on Principal Components (HCPC) for phenotyping.
- Logistic regression identified prognostic factors for disease chronicity.
Main Results:
- Two distinct phenotypic clusters were identified: Cluster 1 (minimal extrapulmonary involvement) and Cluster 2 (multi-organ disease).
- Cluster 2 showed higher frequencies of liver, musculoskeletal, spleen, cardiac, and skin involvement.
- Arthritis was strongly associated with increased chronicity risk (OR 17.02), while lymph node involvement alone was protective (OR 0.17).
Conclusions:
- Cluster analysis revealed two distinct sarcoidosis phenotypes.
- A potential third, arthritis-predominant phenotype emerged in sensitivity analysis.
- Lone lymphadenopathy (intrathoracic or extrathoracic) appears significantly protective against sarcoidosis chronicity.
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