Clinical phenotypes and prediction of chronicity in sarcoidosis using cluster analysis in a prospective cohort of 694 patients
- PMID: 32331839
- DOI: 10.1016/j.ejim.2020.04.024
Clinical phenotypes and prediction of chronicity in sarcoidosis using cluster analysis in a prospective cohort of 694 patients
Abstract
Background: Sarcoidosis is a heterogeneous disease with high variability in natural history and clinical spectrum. The study aimed to reveal different clinical phenotypes of patients with similar characteristics and prognosis.
Methods: Cluster analysis including 26 phenotypic variables was performed in a large cohort of 694 sarcoidosis patients, collected and followed-up from 1976 to 2018 at Bellvitge University Hospital, Barcelona, Spain.
Results: Six homogeneous groups were identified after cluster analysis: C1 (n=47; 6.8%), C2 (n=85; 12.2%), C3 (n=153; 22%), C4 (n=29; 4.2%), C5 (n=168; 24.2%), and C6 (n=212; 30.5%). Presence of bilateral hilar lymphadenopathy (BHL) ranged from 65.5% (C4) to 97.9% (C1). Patients with Löfgren syndrome (LS) were distributed across 3 phenotypes (C1, C2, and C3). In contrast, phenotypes with pulmonary (PS) and/or extrapulmonary sarcoidosis (EPS) were represented by groups C4 (PS 100% with no EPS), C5 (PS 88.7% plus EPS), and C6 (EPS). EPS was concentrated in groups C5 (skin lesions, peripheral and abdominal lymph nodes, and hepatosplenic involvement) and C6 (skin lesions, peripheral lymph nodes, and neurological and ocular involvement). Unlike patients from LS groups, most patients with PS and/or EPS were treated with immunosuppressive therapy, and evolved to chronicity in higher proportion. Finally, the cluster model worked moderately well as a predictive model of chronicity (AUC=0.705).
Conclusion: Cluster analysis identified 6 different clinical patterns with similar phenotypic variables and predicted chronicity in our large cohort of patients with sarcoidosis. Classification of sarcoidosis into phenotypes with prognostic value may help physicians to improve the efficacy of clinical decisions.
Keywords: Cluster analysis; Phenotype; Prognosis; Sarcoidosis.
Copyright © 2020 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.
Conflict of interest statement
Declaration of Competing Interest The authors declare no conflicts of interest. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Comment in
-
Comment to: Cluster analysis for clinical sarcoidosis' phenotyping.Eur J Intern Med. 2020 Aug;78:142. doi: 10.1016/j.ejim.2020.05.024. Epub 2020 May 29. Eur J Intern Med. 2020. PMID: 32482598 No abstract available.
-
Cluster analysis for clinical sarcoidosis' phenotyping.Eur J Intern Med. 2020 Jul;77:32. doi: 10.1016/j.ejim.2020.05.010. Epub 2020 May 29. Eur J Intern Med. 2020. PMID: 32482601 No abstract available.
MeSH terms
LinkOut - more resources
Full Text Sources
Medical
Miscellaneous