The Kellgren Centre for Rheumatology, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
Lupus. 2023 Aug;32(9):1043-1055. doi: 10.1177/09612033231183273. Epub 2023 Jul 18.
We aimed to identify factors associated with a significant reduction in SLE disease activity over 12 months assessed by the BILAG Index.
In an international SLE cohort, we studied patients from their 'inception enrolment' visit. We also defined an 'active disease' cohort of patients who had active disease similar to that needed for enrolment into clinical trials. Outcomes at 12 months were; Major Clinical Response (MCR: reduction to classic BILAG C in all domains, steroid dose of ≤7.5 mg and SLEDAI ≤ 4) and 'Improvement' (reduction to ≤1B score in previously active organs; no new BILAG A/B; stable or reduced steroid dose; no increase in SLEDAI). Univariate and multivariate logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) and cross-validation in randomly split samples were used to build prediction models.
'Inception enrolment' ( = 1492) and 'active disease' ( = 924) patients were studied. Models for MCR performed well (ROC AUC = .777 and .732 in the inception enrolment and active disease cohorts, respectively). Models for Improvement performed poorly (ROC AUC = .574 in the active disease cohort). MCR in both cohorts was associated with anti-malarial use and inversely associated with active disease at baseline (BILAG or SLEDAI) scores, BILAG haematological A/B scores, higher steroid dose and immunosuppressive use.
Baseline predictors of response in SLE can help identify patients in clinic who are less likely to respond to standard therapy. They are also important as stratification factors when designing clinical trials in order to better standardize overall usual care response rates.
我们旨在确定与通过 BILAG 指数评估的 12 个月内 SLE 疾病活动度显著降低相关的因素。
在一个国际 SLE 队列中,我们研究了从“初始入组”就诊的患者。我们还定义了一个“活动性疾病”队列,该队列的患者具有类似于临床试验入组所需的活动性疾病。12 个月时的结局为:主要临床缓解(MCR:所有领域的疾病减少至经典 BILAG C,类固醇剂量≤7.5mg,SLEDAI≤4)和“改善”(减少至先前活动器官≤1B 评分;无新的 BILAG A/B;稳定或减少的类固醇剂量;SLEDAI 无增加)。使用最小绝对值收缩和选择算子(LASSO)和随机拆分样本的交叉验证的单变量和多变量逻辑回归来构建预测模型。
研究了“初始入组”(=1492)和“活动性疾病”(=924)患者。MCR 的模型表现良好(ROC AUC 在初始入组和活动性疾病队列中分别为.777 和.732)。改善模型表现不佳(ROC AUC 在活动性疾病队列中为.574)。两个队列中的 MCR 均与抗疟药物的使用相关,与基线(BILAG 或 SLEDAI)评分、BILAG 血液学 A/B 评分、更高的类固醇剂量和免疫抑制药物的使用呈负相关。
SLE 反应的基线预测因子有助于识别出对标准治疗反应不佳的临床患者。当设计临床试验以更好地标准化总体常规护理反应率时,它们也是重要的分层因素。