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Clinical phenotypes and prediction of chronicity in sarcoidosis using cluster analysis in a prospective cohort of 694 patients

  • Manuel Rubio-Rivas
    Affiliations
    Autoimmune Diseases Unit, Department of Internal Medicine, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, University of Barcelona, Barcelona, Spain
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  • Xavier Corbella
    Affiliations
    Autoimmune Diseases Unit, Department of Internal Medicine, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, University of Barcelona, Barcelona, Spain

    Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, Barcelona, Spain

    Evaluation of Health Determinants and Health Policies Group, Hestia Chair in Integrated Health and Social Care, Barcelona, Spain
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Published:April 21, 2020DOI:https://doi.org/10.1016/j.ejim.2020.04.024

      Highlights

      • We identified six phenotype subgroups
      • Löfgren's syndrome comprised 3 clusters (C1, C2, and C3)
      • C4 cluster comprised patients with pulmonary sarcoidosis
      • C5 cluster comprised patients with abdominal and pulmonary sarcoidosis
      • C6 cluster comprised patients with stage I plus extrapulmonary sarcoidosis

      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

      Abbreviations:

      AA (arthralgias/arthritis), AUC (area under curve), BHL (bilateral hilar lymphadenopathy), COS (clinical outcome status), CPI (composite physiology index), DLco (diffusing capacity for carbon monoxide), EN (erythema nodosum), EPS (extrapulmonary sarcoidosis), FEV1 (forced expiratory volume in 1st second), FVC (forced vital capacity), LS (Löfgren's syndrome), MPAD/AAD (main pulmonary artery diameter/ascending aorta diameter ratio), PAI (periarticular ankle inflammation), PS (pulmonary sarcoidosis), ROC (receiver operating characteristic), SACE (serum angiotensin-converting enzyme), SURT (sarcoidosis of the upper respiratory tract)
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