ArticleTherapeutic advances in respiratory disease
Decoding sarcoidosis chronicity through phenotypic profiling.
Article in Therapeutic advances in respiratory disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundSarcoidosis is a heterogeneous granulomatous disease of unknown aetiology, characterised by a highly variable clinical behaviour. While some patients experience a self‑limited course, others develop chronic and relapsing disease. At present, no precise phenotyping strategy exists in clinical practice to reliably predict which patients will progress to chronicity.
objectivesThe aim of this study was to identify distinct phenotypic clusters sharing common clinical characteristics and to evaluate the predictive value of these clusters for disease outcomes.
designThis is a retrospective, single-center study. Histologically confirmed sarcoidosis patients (
methodsMultiple correspondence analysis (MCA) followed by hierarchical clustering on principal components (HCPC) was performed to identify phenotypic clusters. Logistic regression was performed to identify the prognostic factors of chronicity.
resultsA total of 68 consecutive patients with sarcoidosis were included in the study. The mean age at diagnosis was 57.6 ± 11.1 years, with the majority being females (61.8%). Thoracic involvement, including either intrathoracic lymph nodes and/or the lungs, was the most frequently detected. Overall, fatigue, cough, and arthralgia were among the most frequently reported symptoms. Two phenotypic clusters were identified, including 63 (92.6%) and 5 (7.4%) patients. Cluster 1 was characterised by minimal extrapulmonary involvement, whereas Cluster 2 showed a higher frequency of multi-organ disease, including liver (80%), musculoskeletal (75%), spleen (67%), cardiac (50%) and skin (43%) involvement. Cluster stability was moderate to weak. The clustering phenotype was not associated with chronicity. However, involvement of lymph nodes only was associated with reduced odds of chronicity (OR 0.17, 95% CI 0.02-0.69), while arthritis was strongly associated with increased chronicity risk (OR 17.02, 95% CI 2.04-471.07). Exploratory 3-cluster analysis suggested a potential arthritis-predominant phenotype, although of low stability.
conclusionTwo distinct phenotypes in sarcoidosis are identified by using cluster analysis. In a sensitivity analysis that allowed for three clusters, a third cluster, characterised by the presence of arthritis and predominant eye and skin involvement, emerged. Interestingly, the presence of lone intrathoracic or extrathoracic lymphadenopathy appears to be significantly protective against chronicity.
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