基于炎症的生物标志物预测系统性红斑狼疮肾炎

N. Oruçoğlu
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引用次数: 0

摘要

背景/目的:炎症是系统性红斑狼疮(SLE)肾炎病理生理的重要组成部分。基于免疫的评分,如中性粒细胞淋巴细胞和血小板淋巴细胞比率(分别为NLR和PLR)已被认为是SLE炎症和预后的预测因子。本研究旨在探讨系统性免疫炎症指数(SII)、炎症预后指数(IPI)和系统性炎症反应指数(SIRI)在SLE和狼疮性肾炎(LN)中的价值。方法:本病例对照研究包括108名新诊断的SLE患者(分为两个亚组,其中34名活检证实的LN患者和74名无肾炎的患者)和108名年龄和性别匹配的健康对照组,这些患者于2015年10月至2020年6月在我们的门诊就诊。排除恶性肿瘤、淋巴增生性和血液病、活动性感染和SLE以外的自身免疫性疾病患者。基于炎症的生物标志物在疾病首次出现时和任何药物治疗前计算。SII为中性粒细胞/淋巴细胞×血小板,SIRI为中性粒细胞×单核细胞/淋巴细胞,IPI为CRP × NLR/血清白蛋白。采用系统性红斑狼疮疾病活动性指数2000 (SLEDAI-2K)来衡量疾病活动性。采用受试者工作特征(ROC)曲线评估SII、SIRI、NLR、PLR和IPI区分SLE患者有无肾炎的能力。分析基于炎症的评分(SII、SIRI、IPI、NLR)与SLE患者疾病活动性和实验室数据的相关性。结果:SLE患者SII、SIRI、IPI明显高于健康对照组(P=0.003、P=0.019、P<0.001),合并肾炎患者SII、SIRI、IPI明显高于未合并肾炎患者(P<0.001、P=0.009、P=0.007)。SII、SIRI、IPI鉴别SLE有无肾炎的曲线下面积(AUC)分别为0.748、0.690、0.663。SII、SIRI和IPI预测LN的临界值为552.25(灵敏度:64.7%;特异性:64.9%;P<0.001), 1.08(敏感性:61.8%;特异性:62.2%;P=0.002), 4.48(敏感性:61.8%;特异性,62.2%;分别P = 0.007)。结论:SII, SIRI和IPI可能是SLE和SLE患者肾炎存在的有价值和有前途的炎症生物标志物。在我们的研究中,SII被发现是基于炎症的生物标志物中最可靠的SLE预测因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inflammation-based biomarkers for the prediction of nephritis in systemic lupus erythematosus
Background/Aim: Inflammation is a crucial component in the pathophysiology of systemic lupus erythematosus (SLE) nephritis. Immune-based scores, such as the neutrophil-lymphocyte and the platelet-lymphocyte ratios (NLR and PLR, respectively) have been suggested as predictors of inflammation and prognosis in SLE. This study aimed to investigate the value of the systemic immune-inflammation index (SII), inflammatory prognostic index (IPI), and systemic inflammatory response index (SIRI) in SLE and lupus nephritis (LN). Methods: This case-control study consisted of 108 newly diagnosed SLE patients (separated into two subgroups, which included 34 patients with biopsy-proven LN and 74 without nephritis) and 108 age- and gender-matched healthy controls who presented to our outpatient clinic between October 2015 and June 2020. Patients with malignancy, lymphoproliferative and hematologic disorders, active infection, and autoimmune diseases other than SLE were excluded. Inflammation-based biomarkers were calculated at the first presentation of the disease and before any medication was administered. SII was calculated as Neutrophil/Lymphocyte x Platelet, SIRI as Neutrophil x Monocyte/Lymphocyte, and IPI as CRP x NLR/serum albumin. The Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) was used to measure disease activity. The capability of SII, SIRI, NLR, PLR, and IPI to distinguish between SLE patients with or without nephritis was assessed using receiver operating characteristic (ROC) curves. Correlations of inflammation-based scores (SII, SIRI, IPI, NLR) with disease activity and laboratory data of SLE patients were analyzed. Results: SII, SIRI, and IPI were significantly higher in SLE patients than in healthy controls (P=0.003, P=0.019, and P<0.001, respectively) and also significantly higher in patients with nephritis than in those without (P<0.001, P=0.009, and P=0.007, respectively). The area under the curve (AUC) for SII, SIRI, and IPI in terms of differentiating SLE patients with or without nephritis was 0.748, 0.690, and 0.663, respectively. The cut-off value of SII, SIRI, and IPI to predict LN was 552.25 (sensitivity: 64.7%; specificity: 64.9%; P<0.001), 1.08 (sensitivity: 61.8%; specificity: 62.2%; P=0.002), and 4.48 (sensitivity: 61.8%; specificity, 62.2%; P=0.007), respectively. Conclusion: SII, SIRI, and IPI may be valuable and promising inflammation-based biomarkers in SLE and for the presence of nephritis in SLE patients. SII was found to be the most reliable predictor of SLE among the inflammation-based biomarkers in our study.
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