Identifying clinical subgroups in IgG4-related disease patients using cluster analysis and IgG4-RD composite score
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RESEARCH ARTICLE
Open Access
Identifying clinical subgroups in IgG4related disease patients using cluster analysis and IgG4-RD composite score Jieqiong Li1†, Yu Peng1†, Yuelun Zhang2, Panpan Zhang1, Zheng Liu1, Hui Lu1, Linyi Peng1, Liang Zhu3, Huadan Xue3, Yan Zhao1, Xiaofeng Zeng1, Yunyun Fei1* and Wen Zhang1*
Abstract Background: To explore the clinical patterns of patients with IgG4-related disease (IgG4-RD) based on laboratory tests and the number of organs involved. Methods: Twenty-two baseline variables were obtained from 154 patients with IgG4-RD. Based on principal component analysis (PCA), patients with IgG4-RD were classified into different subgroups using cluster analysis. Additionally, IgG4-RD composite score (IgG4-RD CS) as a comprehensive score was calculated for each patient by principal component evaluation. Multiple linear regression was used to establish the “IgG4-RD CS” prediction model for the comprehensive assessment of IgG4-RD. To evaluate the value of the IgG4-RD CS in the assessment of disease severity, patients in different IgG4-RD CS groups and in different IgG4-RD responder index (RI) groups were compared. Results: PCA indicated that the 22 baseline variables of IgG4-RD patients mainly consisted of inflammation, high serum IgG4, multi-organ involvement, and allergy-related phenotypes. Cluster analysis classified patients into three groups: cluster 1, inflammation and immunoglobulin-dominant group; cluster 2, internal organs-dominant group; and cluster 3, inflammation and immunoglobulin-low with superficial organs-dominant group. Moreover, there were significant differences in serum and clinical characteristics among subgroups based on the CS and RI scores. IgG4-RD CS had a similar ability to assess disease severity as RI. The “IgG4-RD CS” prediction model was established using four independent variables including lymphocyte count, eosinophil count, IgG levels, and the total number of involved organs. Conclusion: Our study indicated that newly diagnosed IgG4-RD patients could be divided into three subgroups. We also showed that the IgG4-RD CS had the potential to be complementary to the RI score, which can help assess disease severity. Keywords: IgG4-related disease, Laboratory test, Organs involved, Cluster analysis, IgG4-RD CS
Background IgG4-related disease (IgG4-RD) is a multi-organ immunemediated condition characterized by tumefactive lesions, a dense lymphoplasmacytic infiltrate rich in IgG4-positive plasma cells, storiform fibrosis, and, often but not always, elevated serum IgG4 concentrations [1–3]. The * Correspondence: [email protected]; [email protected] † Jieqiong Li and Yu Peng contributed equally to this work. 1 Department of Rheumatology, Peking Union Medical College Hospital, Clinical Immunology Center, Beijing, China Full list of author information is available at the end of the article
comprehensive diagnostic criteria for IgG4-RD were published in 2011 by the Umehara and Okazaki teams [4]. The IgG4-RD responder index (RI) is a disease activity tool modele
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