Predicting the Risk of Pulmonary Arterial Hypertension in Systemic Lupus Erythematosus: A Chinese Systemic Lupus Erythematosus Treatment and Research Group Cohort Study
Jingge Qu, Mengtao Li, Yanhong Wang, Xinwang Duan, Hui Luo, Cheng Zhao, Feng Zhan, Zhenbiao Wu, Hongbin Li, Min Yang, Jian Xu, Wei Wei, Lijun Wu, Yongtai Liu, Hanxiao You, Junyan Qian, Xiaoxi Yang, Can Huang, Jiuliang Zhao, Qian Wang, Xiaomei Leng, Xinping Tian, Yan Zhao, Xiaofeng Zeng
Abstract
OBJECTIVE: Pulmonary arterial hypertension (PAH) is a life-threatening complication of systemic lupus erythematosus (SLE). However, there is no algorithm to identify those at high risk. This study was undertaken to develop a prediction model for PAH in patients with lupus that provides individualized risk estimates. METHODS: A multicenter, longitudinal cohort study was undertaken from January 2003 to January 2020. The study collected data on 3,624 consecutively evaluated patients diagnosed as having SLE. The diagnosis of PAH was confirmed by right-sided heart catheterization. Cox proportional hazards regression and least absolute shrinkage and selection operator were used to fit the model. Model discrimination, calibration, and decision curve analysis were performed for validation. RESULTS: Ninety-two lupus patients (2.54%) developed PAH during a median follow-up of 4.84 years (interquartile range 2.42-8.84). The final prediction model included 5 clinical variables (acute/subacute cutaneous lupus, arthritis, renal disorder, thrombocytopenia, and interstitial lung disease) and 3 autoantibodies (anti-RNP, anti-Ro/SSA and anti-La/SSB). A 10-year PAH probability-predictive nomogram was established. The model was internally validated by Harrell's concordance index (0.78), the Brier score (0.03), and a satisfactory calibration curve. According to the net benefit and predicted probability thresholds, we recommend annual screening in high-risk (>4.62%) lupus patients. CONCLUSION: We developed a risk stratification model using routine clinical assessments. This new tool may effectively predict the future risk of PAH in patients with SLE.