Predicting the Risk of Cardiovascular and Cerebrovascular Event in Systemic Lupus Erythematosus: a Chinese SLE Treatment and Research Group Study XXVI

Overview

Journal RMD Open

Publisher BMJ Publishing Group

Specialty Rheumatology

Date 2024 Sep 23

PMID 39313305

Authors

Can Huang

Yutong Li

Ziqian Wang

Shudian Lin

Jiu-Liang Zhao

Qian Wang

Xinping Tian

Yanhong Wang

Xinwang Duan

Yongfu Wang

Cheng Zhao

Zhenbiao Wu

Jian Xu

Chen Han

Min Yang

Rui Wu

Xiaofeng Zeng

Mengtao Li

Affiliations

Soon will be listed here.

Abstract

Objective: Patients with systemic lupus erythematosus (SLE) have an increased risk of cardiovascular and cerebrovascular events (CCEs). Furthermore, CCE was a significant factor contributing to mortality in patients with SLE. However, no clinical model exists that can predict which patients are at high risk. The purpose of this study was to develop a practical model for predicting the risk of CCE in people with SLE.

Methods: This study was based on the Chinese SLE Treatment and Research Group cohort. A total of 2399 patients, who had a follow-up period of over 3 years and were diagnosed with SLE for less than 1 year at the start of the study, were included. Cox proportional hazards regression and least absolute shrinkage and selection operator regression were used to establish the model. Internal validation was performed, and the predictive power of the model was evaluated.

Results: During the follow-up period, 93 patients had CCEs. The prediction model included nine variables: male gender, smoking, hypertension, age of SLE onset >40, cutaneous involvement, arthritis, anti-β2GP1 antibody positivity, high-dose glucocorticoids and hydroxychloroquine usage. The model's C index was 0.801. Patients with a prognostic index over 0.544 were classified into the high-risk group.

Conclusion: We have developed a predictive model that uses clinical indicators to assess the probability of CCE in patients diagnosed with SLE. This model has the ability to precisely predict the risk of CCE in patients with SLE. We recommended using this model in the routine assessment of patients with SLE.

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