Risk prediction of new-onset thrombocytopenia in patients with systemic lupus erythematosus: a multicenter prospective cohort study based on Chinese SLE treatment and research group (CSTAR) registry

IF 4.9 2区医学 Q1 Medicine

Arthritis Research & Therapy Pub Date : 2024-12-27 DOI:10.1186/s13075-024-03460-0

Yupei Zhang, Nan Jiang, Xinwang Duan, Jian Xu, Lijun Wu, Wei Wei, Weiguo Xiao, Li Luo, Zhenyu Jiang, Yanhong Wang, Jiuliang Zhao, Qian Wang, Xinping Tian, Mengtao Li, Xiaofeng Zeng

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Abstract

Thrombocytopenia (TP) is a hematological manifestation of systemic lupus erythematosus (SLE) and is associated with unfavorable prognostic outcomes. This study aimed to develop a risk prediction model for new-onset TP in SLE patients. Based on the multicenter prospective Chinese SLE Treatment and Research Group (CSTAR) registry, newly diagnosed SLE patients without TP at registration were enrolled. The least absolute shrinkage and selection operator (LASSO) method was used for variable selection. The final model was developed using multivariate Cox regression and displayed as a nomogram. Internal validation was achieved using enhanced Bootstrap resampling. During follow-up, thrombocytopenia developed in 80 (3.52%) of 2270 lupus patients. The final risk prediction model incorporated six predictors: baseline SDI score ≥ 1 (HR 2.207, 95% CI 1.350–3.609, p = 0.002), hemolytic anemia (HR 1.953, 95% CI 1.017–3.750, p = 0.044), low complement level (HR 2.351, 95% CI 1.004–5.505, p = 0.049), positive anti-β2GPI antibody (HR 1.805, 95% CI 1.084–3.004, p = 0.024), positive Coombs test (HR 1.878, 95% CI 1.123–3.141, p = 0.017), and positive anti-histone antibody (HR 1.595, 95% CI 1.017–2.587, p = 0.059). The model’s performance was indicated by C-index values for risk prediction at one, two, and three years, which were 0.741 (0.660–0.823), 0.730 (0.655–0.805), and 0.710 (0.643–0.777), respectively; and Brier scores of 0.018 (0.012–0.024), 0.025 (0.017–0.032), and 0.037 (0.027–0.046), respectively. Calibration curves were drawn and situated near the diagonal line. This study developed the first risk prediction model for TP onset in lupus patients. Patients with baseline organ damage, hemolytic anemia, low complement, positive anti-histone antibody, positive anti-β2GPI antibody, or positive Coombs test were identified as being at high risk for thrombocytopenia and require further clinical attention.

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系统性红斑狼疮患者新发血小板减少的风险预测：基于中国SLE治疗和研究组（CSTAR）登记的多中心前瞻性队列研究

血小板减少症（TP）是系统性红斑狼疮（SLE）的血液学表现，与不良预后相关。本研究旨在建立SLE患者新发TP的风险预测模型。基于多中心前瞻性中国SLE治疗与研究小组（CSTAR）注册表，入组新诊断的SLE患者，注册时无TP。采用最小绝对收缩和选择算子（LASSO）方法进行变量选择。最后的模型是使用多变量Cox回归建立的，并显示为nomogram。内部验证是通过增强的Bootstrap重采样实现的。随访期间，2270例狼疮患者中有80例（3.52%）出现血小板减少症。最终的风险预测模型包含6个预测因子：基线SDI评分≥1 （HR 2.207, 95% CI 1.350 ~ 3.609, p = 0.002）、溶血性贫血（HR 1.953, 95% CI 1.017 ~ 3.750, p = 0.044）、低补体水平（HR 2.351, 95% CI 1.004 ~ 5.505, p = 0.049）、抗β 2gpi抗体阳性（HR 1.805, 95% CI 1.084 ~ 3.004, p = 0.024）、Coombs试验阳性（HR 1.878, 95% CI 1.123 ~ 3.141, p = 0.017）、抗组蛋白抗体阳性（HR 1.595, 95% CI 1.017 ~ 2.587, p = 0.059）。1年、2年和3年的风险预测c指数值分别为0.741（0.66 - 0.823）、0.730（0.655-0.805）和0.710(0.643-0.777)，表明模型的性能；Brier评分分别为0.018（0.012-0.024）、0.025（0.017-0.032）和0.037（0.027-0.046）。绘制校准曲线并置于对角线附近。本研究建立了首个狼疮患者TP发病风险预测模型。基线器官损害、溶血性贫血、低补体、抗组蛋白抗体阳性、抗β 2gpi抗体阳性或Coombs试验阳性的患者被认为是血小板减少的高危人群，需要进一步的临床关注。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Arthritis Research & Therapy RHEUMATOLOGY-

CiteScore

8.60

自引率

2.00%

发文量

261

审稿时长

14 weeks

期刊介绍： Established in 1999, Arthritis Research and Therapy is an international, open access, peer-reviewed journal, publishing original articles in the area of musculoskeletal research and therapy as well as, reviews, commentaries and reports. A major focus of the journal is on the immunologic processes leading to inflammation, damage and repair as they relate to autoimmune rheumatic and musculoskeletal conditions, and which inform the translation of this knowledge into advances in clinical care. Original basic, translational and clinical research is considered for publication along with results of early and late phase therapeutic trials, especially as they pertain to the underpinning science that informs clinical observations in interventional studies.