Arthritis Research & Therapy | |
Identifying clinical subgroups in IgG4-related disease patients using cluster analysis and IgG4-RD composite score | |
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
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202104271107412ZK.pdf | 1730KB | download |