类风湿关节炎患者生物和靶向合成疾病改善抗风湿药物治疗的疾病活动轨迹差异

IF 4.4 2区 医学 Q1 RHEUMATOLOGY
Bon San Koo, Seongho Eun, Kichul Shin, Seokchan Hong, Yong-Gil Kim, Chang-Keun Lee, Bin Yoo, Ji Seon Oh
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引用次数: 4

摘要

背景:本研究的目的是通过基于轨迹的聚类,根据疾病活动趋势对类风湿关节炎(RA)患者进行分层,并根据轨迹组确定生物和靶向合成疾病改善抗风湿药物(DMARDs)治疗反应的影响因素。方法:我们分析了来自韩国风湿病学院生物制剂和靶向治疗登记处的全国性RA队列数据。接受二线生物制剂和靶向合成dmard治疗的患者也包括在内。采用轨迹建模进行聚类,对疾病活动趋势进行分组。利用机器学习模型的SHAP (SHapley Additive explanation)值对每个轨迹进行了影响因素的研究。结果:688例RA患者的疾病活动性趋势可分为4组:疾病活动性快速下降并稳定(第1组,n = 319)、快速下降后上升(第2组,n = 36)、缓慢持续下降(第3组,n = 290)、疾病活动性未下降(第4组,n = 43)。SHAP图显示,与1组相比,2组最重要的特征是基线红细胞沉降率(ESR)、强的松龙剂量和28关节疾病活动性评分(DAS28) (SHAP值分别为0.308、0.157和0.103)。与1组相比,3组最重要的特征是基线ESR、DAS28和估计肾小球滤过率(eGFR) (SHAP值分别为0.175、0.164和0.042)。与1组相比,4组最重要的特征是基线DAS28、ESR和血尿素氮(BUN) (SHAP值分别为0.387、0.153、0.144)。结论:基于轨迹的方法可用于类风湿关节炎患者生物和靶向合成dmard治疗反应的聚类。此外,基线DAS28, ESR,泼尼松龙剂量,eGFR和BUN是4年轨迹的重要影响因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis.

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis.

Differences in trajectory of disease activity according to biologic and targeted synthetic disease-modifying anti-rheumatic drug treatment in patients with rheumatoid arthritis.

Background: The purpose of this study was to stratify patients with rheumatoid arthritis (RA) according to the trend of disease activity by trajectory-based clustering and to identify contributing factors for treatment response to biologic and targeted synthetic disease-modifying anti-rheumatic drugs (DMARDs) according to trajectory groups.

Methods: We analyzed the data from a nationwide RA cohort from the Korean College of Rheumatology Biologics and Targeted Therapy registry. Patients treated with second-line biologic and targeted synthetic DMARDs were included. Trajectory modeling for clustering was used to group the disease activity trend. The contributing factors using the machine learning model of SHAP (SHapley Additive exPlanations) values for each trajectory were investigated.

Results: The trends in the disease activity of 688 RA patients were clustered into 4 groups: rapid decrease and stable disease activity (group 1, n = 319), rapid decrease followed by an increase (group 2, n = 36), slow and continued decrease (group 3, n = 290), and no decrease in disease activity (group 4, n = 43). SHAP plots indicated that the most important features of group 2 compared to group 1 were the baseline erythrocyte sedimentation rate (ESR), prednisolone dose, and disease activity score with 28-joint assessment (DAS28) (SHAP value 0.308, 0.157, and 0.103, respectively). The most important features of group 3 compared to group 1 were the baseline ESR, DAS28, and estimated glomerular filtration rate (eGFR) (SHAP value 0.175, 0.164, 0.042, respectively). The most important features of group 4 compared to group 1 were the baseline DAS28, ESR, and blood urea nitrogen (BUN) (SHAP value 0.387, 0.153, 0.144, respectively).

Conclusions: The trajectory-based approach was useful for clustering the treatment response of biologic and targeted synthetic DMARDs in patients with RA. In addition, baseline DAS28, ESR, prednisolone dose, eGFR, and BUN were important contributing factors for 4-year trajectories.

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来源期刊
CiteScore
8.30
自引率
2.00%
发文量
261
审稿时长
2.3 months
期刊介绍: Established in 1999, Arthritis Research and Therapy is an international, open access, peer-reviewed journal, publishing original articles in the area of musculoskeletal research and therapy as well as, reviews, commentaries and reports. A major focus of the journal is on the immunologic processes leading to inflammation, damage and repair as they relate to autoimmune rheumatic and musculoskeletal conditions, and which inform the translation of this knowledge into advances in clinical care. Original basic, translational and clinical research is considered for publication along with results of early and late phase therapeutic trials, especially as they pertain to the underpinning science that informs clinical observations in interventional studies.
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