The Kellgren Centre for Rheumatology, NIHR Manchester Biomedical Research Centre, Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Lupus Sci Med. 2022 May;9(1). doi: 10.1136/lupus-2021-000584.
To identify predictors of overall lupus and lupus nephritis (LN) responses in patients with LN.
Data from the Aspreva Lupus Management Study (ALMS) trial cohort was used to identify baseline predictors of response at 6 months. Endpoints were major clinical response (MCR), improvement, complete renal response (CRR) and partial renal response (PRR). Univariate and multivariate logistic regressions with least absolute shrinkage and selection operator (LASSO) and cross-validation in randomly split samples were utilised. Predictors were ranked by the percentage of times selected by LASSO and prediction performance was assessed by the area under the receiver operating characteristics (AUROC) curve.
We studied 370 patients in the ALMS induction trial. Improvement at 6 months was associated with older age (OR=1.03 (95% CI: 1.01 to 1.05) per year), normal haemoglobin (1.85 (1.16 to 2.95) vs low haemoglobin), active lupus (British Isles Lupus Assessment Group A or B) in haematological and mucocutaneous domains (0.61 (0.39 to 0.97) and 0.50 (0.31 to 0.81)), baseline damage (SDI>1 vs =0) (0.38 (0.16 to 0.91)) and 24-hour urine protein (0.63 (0.50 to 0.80)). LN duration 2-4 years (0.43 (0.19 to 0.97) vs <1 year) and 24-hour urine protein (0.63 (0.45 to 0.89)) were negative predictors of CRR. LN duration 2-4 years (0.45 (0.24 to 0.83) vs <1 year) negatively predicted PRR. The AUROCs of models for improvement, CRR and PRR were 0.56, 0.55 and 0.51 respectively.
Baseline variables predicted 6-month outcomes in patients with SLE. While the modest performance of models emphasises the need for new biomarkers to advance this field, the factors identified can help identify those patients who may require novel treatment strategies.
确定狼疮肾炎 (LN) 患者总体狼疮和 LN 反应的预测因素。
使用来自 Aspreva Lupus Management Study (ALMS) 试验队列的数据,确定 6 个月时反应的基线预测因素。终点为主要临床反应 (MCR)、改善、完全肾脏反应 (CRR) 和部分肾脏反应 (PRR)。使用最小绝对收缩和选择算子 (LASSO) 和随机拆分样本的交叉验证进行单变量和多变量逻辑回归。通过 LASSO 选择的次数对预测因子进行排序,并通过接收者操作特征 (ROC) 曲线下面积 (AUROC) 评估预测性能。
我们研究了 ALMS 诱导试验中的 370 名患者。6 个月时的改善与年龄较大(每增加 1 岁,OR=1.03 (95% CI: 1.01 至 1.05))、血红蛋白正常(1.85 (1.16 至 2.95) 与低血红蛋白)、血液学和黏膜皮肤域中的活动性狼疮(不列颠群岛狼疮评估组 A 或 B)(0.61 (0.39 至 0.97) 和 0.50 (0.31 至 0.81))、基线损伤 (SDI>1 与 =0)(0.38 (0.16 至 0.91))和 24 小时尿蛋白(0.63 (0.50 至 0.80))相关。LN 持续时间 2-4 年(0.43 (0.19 至 0.97) 与 <1 年)和 24 小时尿蛋白(0.63 (0.45 至 0.89))是 CRR 的负预测因子。LN 持续时间 2-4 年(0.45 (0.24 至 0.83) 与 <1 年)负预测 PRR。改善、CRR 和 PRR 模型的 AUROCs 分别为 0.56、0.55 和 0.51。
基线变量预测了 SLE 患者 6 个月的结局。虽然模型的表现并不理想,但强调了需要新的生物标志物来推动这一领域的发展,而确定的因素可以帮助识别那些可能需要新治疗策略的患者。