Identifying clinical subgroups in IgG4-related disease patients using cluster analysis and IgG4-RD composite score

Arthritis Research & Therapy

Yuelun Zhang¹  Huadan Xue²  Liang Zhu²  Yunyun Fei³  Yan Zhao³  Hui Lu³  Linyi Peng³  Panpan Zhang³  Wen Zhang³  Xiaofeng Zeng³  Yu Peng³  Jieqiong Li³  Zheng Liu³ 

[1] Central Research Laboratory, Peking Union Medical College Hospital, Beijing, China;Department of Radiology, Peking Union Medical College Hospital, Beijing, China;Department of Rheumatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, National Clinical Research Center for Dermatologic and Immunologic Diseases (NCRC-DID), Key Laboratory of Ministry of Health, Beijing, China;

关键词: IgG4-related disease;    Laboratory test;    Organs involved;    Cluster analysis;    IgG4-RD CS;   

DOI  :  10.1186/s13075-019-2090-9

来源: Springer

【 摘 要 】

BackgroundTo explore the clinical patterns of patients with IgG4-related disease (IgG4-RD) based on laboratory tests and the number of organs involved.MethodsTwenty-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.ResultsPCA 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.ConclusionOur 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.

【 授权许可】

CC BY