Gulati G, Bennett M R, Abulaban K, Song H, Zhang X, Ma Q, Brodsky S V, Nadasdy T, Haffner C, Wiley K, Ardoin S P, Devarajan P, Ying J, Rovin B H, Brunner H I
1 Division of Immunology, Allergy and Rheumatology, University of Cincinnati College of Medicine, USA.
2 Division of Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, USA.
Lupus. 2017 Aug;26(9):927-936. doi: 10.1177/0961203316684212. Epub 2016 Dec 19.
Objectives The renal activity index for lupus (RAIL) score was developed in children with lupus nephritis as a weighted sum of six urine biomarkers (UBMs) (neutrophil gelatinase-associated lipocalin, monocyte chemotactic protein 1, ceruloplasmin, adiponectin, hemopexin and kidney injury molecule 1) measured in a random urine sample. We aimed at prospectively validating the RAIL in adults with lupus nephritis. Methods Urine from 79 adults was collected at the time of kidney biopsy to assay the RAIL UBMs. Using receiver operating characteristic curve analysis, we evaluated the accuracy of the RAIL to discriminate high lupus nephritis activity status (National Institutes of Health activity index (NIH-AI) score >10), from low/moderate lupus nephritis activity status (NIH-AI score ≤10). Results In this mixed racial cohort, high lupus nephritis activity was present in 15 patients (19%), and 71% had proliferative lupus nephritis. Use of the identical RAIL algorithm developed in children resulted in only fair prediction of lupus nephritis activity status of adults (area under the receiver operating characteristic curve (AUC) 0.62). Alternative weightings of the six RAIL UBMs as suggested by logistic regression yielded excellent accuracy to predict lupus nephritis activity status (AUC 0.88). Accuracy of the model did not improve with adjustment of the UBMs for urine creatinine or albumin, and was little influenced by concurrent kidney damage. Conclusions The RAIL UBMs provide excellent prediction of lupus nephritis activity in adults. Age adaption of the RAIL is warranted to optimize its discriminative validity to predict high lupus nephritis activity status non-invasively.
目的 狼疮性肾炎肾脏活动指数（RAIL）评分是针对狼疮性肾炎患儿制定的，通过对随机尿样中6种尿液生物标志物（UBMs）（中性粒细胞明胶酶相关脂质运载蛋白、单核细胞趋化蛋白1、铜蓝蛋白、脂联素、血红素结合蛋白和肾损伤分子1）进行加权求和得出。我们旨在对成人狼疮性肾炎患者进行RAIL评分的前瞻性验证。方法 在肾活检时收集79例成人的尿液，以检测RAIL的UBMs。通过受试者工作特征曲线分析，我们评估了RAIL区分高狼疮性肾炎活动状态（美国国立卫生研究院活动指数（NIH-AI）评分>10）与低/中度狼疮性肾炎活动状态（NIH-AI评分≤10）的准确性。结果 在这个混合种族队列中，15例患者（19%）存在高狼疮性肾炎活动，71%患有增殖性狼疮性肾炎。采用在儿童中开发的相同RAIL算法，对成人狼疮性肾炎活动状态的预测仅为中等水平（受试者工作特征曲线下面积（AUC）为0.62）。逻辑回归建议的6种RAIL UBMs的替代加权法对狼疮性肾炎活动状态的预测具有出色的准确性（AUC为0.88）。对UBMs进行尿肌酐或白蛋白校正后，模型的准确性并未提高，且受并发肾脏损伤的影响较小。结论 RAIL的UBMs能出色地预测成人狼疮性肾炎的活动情况。有必要对RAIL进行年龄适应性调整，以优化其鉴别有效性，从而无创地预测高狼疮性肾炎活动状态。
