Zhang Ji, Song Hanlei, Li Duo, Lv Yinqiu, Chen Bo, Zhou Yin, Ding Xiaokai, Chen Chaosheng
Department of Nephrology, the First Affiliated Hospital of Wenzhou Medical University, Nanbaixiang Street, Ouhai District, Wenzhou, Zhejiang, 325000, People's Republic of China.
Institute of Chronic Kidney Disease, Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Immunol Res. 2021 Jun;69(3):285-294. doi: 10.1007/s12026-021-09201-8. Epub 2021 May 5.
Ambiguities remain regarding the role of clinicopathological characteristics in the early prediction of the prognosis of lupus nephritis (LN). Systemic lupus erythematosus (SLE) patients who completed routine follow-up were identified and retrospectively reviewed for eligible cases. Poor prognosis was defined as all-cause mortality or a persistent decrease of eGFR greater than half the baseline level or progression to end-stage renal disease (ESRD). An optimal Cox regression model was constructed for the early prediction of a poor prognosis for LN. Among the 2163 SLE patients, 376 eligible LN cases were enrolled in the study, with a median follow-up time of 55 [27.0, 87.0] months. The male-to-female ratio was 1:7.2, and 37 patients (9.8%) progressed to the composite endpoint. The ISN/RPS class was significantly associated with proteinuria levels (P-value < 0.001), and class IV/IV + V patients, but not class V patients, had the most severe proteinuria. Our optimal multivariate Cox regression model indicated that sex, ISN/RPS class, tubular atrophy/interstitial fibrosis, serum albumin, tertiles of proteinuria, and their interaction were independently associated with a poor prognosis. ROC analysis and external validation demonstrated that our model was efficient and robust for distinguishing LN patients with a poor prognosis. Our study constructed a robust and early predictive model for convenience in clinical practice to identify poor prognosis in LN patients. We found a significant interaction effect between proteinuria and serum albumin for the prediction of poor prognosis. LN patients with low-level proteinuria and hypoalbuminemia exhibit an increased hazard of progression to poor outcomes.
关于临床病理特征在狼疮性肾炎(LN)预后早期预测中的作用仍存在模糊之处。我们确定了完成常规随访的系统性红斑狼疮(SLE)患者,并对符合条件的病例进行回顾性分析。预后不良定义为全因死亡率、估算肾小球滤过率(eGFR)持续下降超过基线水平的一半或进展为终末期肾病(ESRD)。构建了一个最佳Cox回归模型用于早期预测LN的不良预后。在2163例SLE患者中,376例符合条件的LN病例纳入研究,中位随访时间为55[27.0, 87.0]个月。男女比例为1:7.2,37例患者(9.8%)进展至复合终点。国际肾脏病学会/肾脏病理学会(ISN/RPS)分级与蛋白尿水平显著相关(P值<0.001),IV/IV+V级患者蛋白尿最严重,而V级患者并非如此。我们的最佳多因素Cox回归模型表明,性别、ISN/RPS分级、肾小管萎缩/间质纤维化、血清白蛋白、蛋白尿三分位数及其相互作用与不良预后独立相关。受试者工作特征(ROC)分析和外部验证表明,我们的模型在区分预后不良的LN患者方面有效且稳健。我们的研究构建了一个强大的早期预测模型,便于临床实践中识别LN患者的不良预后。我们发现蛋白尿和血清白蛋白之间存在显著的相互作用效应,可用于预测不良预后。蛋白尿水平低且伴有低白蛋白血症的LN患者进展为不良结局的风险增加。