Prediction of sustained biologic and targeted synthetic DMARD-free remission in rheumatoid arthritis patients.
Prediction of sustained biologic and targeted synthetic DMARD-free remission in rheumatoid arthritis patients.
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DOI：
10.1093/rap/rkab087
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发表时间：
2021
影响因子：
3.1
通讯作者：
Burden AM
中科院分区：
文献类型：
--
作者：
Burkard T;Williams RD;Vallejo-Yagüe E;Hügle T;Finckh A;Kyburz D;Burden AM
目的是开发 RA 停止生物制剂或靶向合成 DMARD (b/tsDMARD) 后持续缓解的预测模型。我们在瑞士临床质量管理登记处（SCQM；2008-2019）中对因病情缓解而停止的 b/tsDMARD RA 治疗疗程进行了一项探索性队列研究。结果是持续≥12个月的无b/tsDMARD缓解。我们应用逻辑回归模型选择算法，使用逐步、前向选择、后向选择和惩罚回归来确定预测持续 b/tsDMARD 无缓解的患者特征。我们比较了模型之间乐观校正的 c 统计量。具有最高 c 统计量的三个模型在 2020 年之前的新 SCQM 数据中得到了验证（验证数据集）。我们确定了 302 例符合条件的发作，其中 177 例 (59%) 实现了持续的无 b/tsDMARD 缓解。分别具有八个、四个和七个变量的两个后向和一个前向选择模型获得了最高的 c 统计量，分别为 c = 0.72、c = 0.70 和 c = 0.69。在验证数据集中（47 个符合条件的剧集），模型的执行结果分别为 c = 0.99、c = 0.80 和 c = 0.74，并且校准良好。最佳模型包括以下八个变量（在 b/tsDMARD 停止时测量）：RA 持续时间、b/tsDMARD 持续时间、其他疼痛/抗炎药物使用、生活质量 (EuroQol)、DAS28-ESR 评分、HAQ 评分、教育以及 RA 持续时间和其他疼痛/抗炎药物使用以及 b/tsDMARD 持续时间和 HAQ 评分之间的相互作用。我们的结果表明，具有多达 8 个独特变量的模型可以高效地预测持续的无 b/tsDMARD 缓解。外部验证是有保证的。
The aim was to develop a prediction model of sustained remission after cessation of biologic or targeted synthetic DMARD (b/tsDMARD) in RA. We conducted an explorative cohort study among b/tsDMARD RA treatment episode courses stopped owing to remission in the Swiss Clinical Quality Management registry (SCQM; 2008–2019). The outcome was sustained b/tsDMARD-free remission of ≥12 months. We applied logistic regression model selection algorithms using stepwise, forward selection, backward selection and penalized regression to identify patient characteristics predictive of sustained b/tsDMARD-free remission. We compared c-statistics corrected for optimism between models. The three models with the highest c-statistics were validated in new SCQM data until 2020 (validation dataset). We identified 302 eligible episodes, of which 177 episodes (59%) achieved sustained b/tsDMARD-free remission. Two backward and one forward selection model, with eight, four and seven variables, respectively, obtained the highest c-statistics corrected for optimism of c = 0.72, c = 0.70 and c = 0.69, respectively. In the validation dataset (47 eligible episodes), the models performed with c = 0.99, c = 0.80 and c = 0.74, respectively, and excellent calibration. The best model included the following eight variables (measured at b/tsDMARD stop): RA duration, b/tsDMARD duration, other pain/anti-inflammatory drug use, quality of life (EuroQol), DAS28-ESR score, HAQ score, education, and interactions of RA duration and other pain/anti-inflammatory drug use and of b/tsDMARD duration and HAQ score. Our results suggest that models with up to eight unique variables may predict sustained b/tsDMARD-free remission with good efficiency. External validation is warranted.
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