Clinical Features and Risk Factors of Rapidly Progressive Systemic Sclerosis in a Single Center in China: Anti-RNA Polymerase III Antibodies as a Predictor.

IF 2 4区 医学 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Qiuxia Yu, Jin Zhang, Liyi Fan, Tianhang Yu, Bingbing Liu, Jian Ding
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引用次数: 1

Abstract

Objectives: Systemic sclerosis (SSc) have been classified in two clinical subsets (diffuse and limited) based on the extend of skin thickening. In this study, we classified a novel subset of SSc defined rapidly progressive systemic sclerosis (RPSSc), which based on the rate of skin thickening progression and the progressive of interstitial lung disease (ILD). We aimed to evaluate RPSSc clinical characteristics and predictive factors in a Chinese single center.

Method: Overall, 75 patients diagnosed with SSc, classified into RPSSc (n = 14) and non-rapidly progressive SSc (non-RPSSc, n = 61) were retrospectively included in the study. Clinical characteristics, disease severity and autoantibodies were collected. Logistic regression, least absolute shrinkage, and selection operator (LASSO) regression analysis was used to identify RPSSc predictors. Receiver operating characteristic (ROC) analysis and Delong test was conducted to evaluate and compare different indexes.

Results: RPSSc rate was 18.7%. ILD (64.3%), cardiac involvement (42.9%) were the most common organ system involvement of RPSSc, while Raynaud's phenomenon incidence significantly decreased. Disease duration (12 vs 72, months), sex (42.9% vs 11.5%, male %), SSc subset (85.7% vs 27.9%, diffuse cutaneous SSc (dsSSc) %), modified Rodnan total skin score (mRSS) (20.5 vs 6), Raynaud's phenomenon (64.3% vs 98.4%), cardiac involvement (42.9% vs 18%), higher incidence with malignancy (28.6% vs 1.6%) and positive anti-RNA polymerase III antibodies (ARA) (64.3% vs 1.6%) were statistically significant differences among the RPSSc groups and non-RPSSc groups (p < 0.05). Univariate analysis showed that positive ARA, male, dsSSc and malignancy were RPSSc risk factors, while long-disease duration, Raynaud's phenomenon was RPSSc protective factors. ARA was the strongest factor associated to RPSSc (OR 108, 95% CI 11.287-1033.327, p < 0.001). LASSO logistic regression model identified six factors: Disease duration, dsSSc, malignancy, cardiac involvement, positivity of ARA were RPSSc risk factors, Raynaud's phenomenon was RPSSc protective factors.

Conclusions: RPSSc is an SSc clinical category which should be accounted for early detection of organ involvement and close follow-up of malignancy. ARA might be used as a predictor for RPSSc and organ involvement.

中国单一中心快速进行性系统性硬化症的临床特征和危险因素:抗rna聚合酶III抗体作为预测因子
目的:根据皮肤增厚的程度,系统性硬化症(SSc)被分为两个临床亚群(弥漫性和局限性)。在这项研究中,我们根据皮肤增厚进展的速度和间质性肺疾病(ILD)的进展,对SSc的一个新子集进行了分类,定义为快速进行性系统性硬化症(RPSSc)。我们的目的是评估中国单中心RPSSc的临床特征和预测因素。方法:回顾性研究75例确诊为SSc的患者,分为RPSSc (n = 14)和非快速进展型SSc (n = 61)。收集临床特征、疾病严重程度及自身抗体。采用Logistic回归、最小绝对收缩和选择算子(LASSO)回归分析来确定RPSSc的预测因子。采用受试者工作特征(ROC)分析和Delong检验对各指标进行评价和比较。结果:RPSSc率为18.7%。ILD(64.3%)、心脏受累(42.9%)是RPSSc最常见的脏器系统受累,雷诺现象发生率显著降低。病程(12个月vs 72个月)、性别(42.9% vs 11.5%,男性%)、SSc亚群(85.7% vs 27.9%,弥漫性皮肤SSc (dsSSc) %)、改良罗德曼皮肤总评分(mRSS) (20.5 vs 6)、Raynaud现象(64.3% vs 98.4%)、心脏受损伤(42.9% vs 18%)、较高的恶性肿瘤发生率(28.6% vs 1.6%)和抗rna聚合酶III抗体(ARA)阳性(64.3% vs 1.6%)在RPSSc组和非RPSSc组之间差异均有统计学意义(p < 0.05)。单因素分析显示,ARA阳性、男性、dsSSc和恶性肿瘤是RPSSc的危险因素,病程长、雷诺现象是RPSSc的保护因素。ARA是与RPSSc相关性最强的因素(OR 108, 95% CI 11.287-1033.327, p < 0.001)。LASSO logistic回归模型确定病程、dsSSc、恶性、心脏受累、ARA阳性为RPSSc的危险因素,雷诺现象为RPSSc的保护因素。结论:RPSSc是SSc的临床分类,应及早发现脏器受累,并密切随访恶性肿瘤。ARA可作为RPSSc和器官受累的预测因子。
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来源期刊
Discovery medicine
Discovery medicine MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
5.40
自引率
0.00%
发文量
80
审稿时长
6-12 weeks
期刊介绍: Discovery Medicine publishes novel, provocative ideas and research findings that challenge conventional notions about disease mechanisms, diagnosis, treatment, or any of the life sciences subjects. It publishes cutting-edge, reliable, and authoritative information in all branches of life sciences but primarily in the following areas: Novel therapies and diagnostics (approved or experimental); innovative ideas, research technologies, and translational research that will give rise to the next generation of new drugs and therapies; breakthrough understanding of mechanism of disease, biology, and physiology; and commercialization of biomedical discoveries pertaining to the development of new drugs, therapies, medical devices, and research technology.
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