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早期中轴型脊柱关节炎的聚类分析预测在外周关节表现存在的情况下预后不良。

Cluster analysis in early axial spondyloarthritis predicts poor outcome in the presence of peripheral articular manifestations.

机构信息

UVSQ, Inserm U1173, Infection et inflammation, Laboratory of Excellence INFLAMEX, Université Paris-Saclay, Montigny-Le-Bretonneux.

Rheumatology Department, AP-HP, Ambroise Paré Hospital, Boulogne-Billancourt.

出版信息

Rheumatology (Oxford). 2022 Aug 3;61(8):3289-3298. doi: 10.1093/rheumatology/keab873.

Abstract

OBJECTIVES

To assess whether two cluster analysis-based axial SpA (axSpA) endotypes (A for purely axial; B for both axial and peripheral) are stable over time and are associated with different long-term disease outcomes.

METHODS

K-means cluster analysis was performed at each visit (until 5 years) on 584 patients from the DESIR cohort, who completed all planned visits, and validated in 232 consecutive axSpA patients from the BeGiant cohort. Cluster stability overtime was assessed by kappa statistics. A generalized linear mixed-effect analysis was applied to compare outcomes between clusters. Classification and regression tree (CART) analysis was performed to determine a decision rule able to assign a given patient to a definite cluster at onset.

RESULTS

Both endotypes remained remarkably stable over time. In the DESIR cohort, patients in cluster B showed higher disease activity, worse functional outcome and higher need for anti-rheumatic drugs than patients in cluster A. CART analysis yielded three main clinical features (arthritis, enthesitis and dactylitis) that accurately determined cluster assignment. These results could be replicated in the Be-GIANT cohort.

CONCLUSION

Cluster-based axSpA endotypes were reproducible in two different cohorts, stable over time and associated with different long-term outcome. The axSpA endotype with additional peripheral disease manifestations is associated with more severe disease and requires more intensive drug therapy.

CLINICAL TRIAL REGISTRATION

clinicaltrials.gov, https://clinicaltrials.gov, NCT01648907.

摘要

目的

评估两种基于聚类分析的中轴型脊柱关节炎(axSpA)亚型(A 型为单纯中轴型;B 型为中轴和外周均受累型)是否具有时间稳定性,并与不同的长期疾病结局相关。

方法

在 DESIR 队列中,对完成所有计划访视的 584 例患者在每个访视点(直至 5 年)进行 K-均值聚类分析,并在来自 BeGiant 队列的 232 例连续 axSpA 患者中进行验证。采用 Kappa 统计评估时间上的聚类稳定性。应用广义线性混合效应分析比较聚类间的结局。采用分类回归树(CART)分析确定一种决策规则,以便在发病时将给定患者分配到确定的聚类中。

结果

两种亚型在整个随访期间均保持高度稳定性。在 DESIR 队列中,与 A 型患者相比,B 型患者的疾病活动度更高,功能结局更差,需要抗风湿药物治疗的可能性更高。CART 分析得出了三个主要的临床特征(关节炎、附着点炎和指(趾)炎),可准确确定聚类归属。这些结果可在 Be-GIANT 队列中复制。

结论

基于聚类的 axSpA 亚型在两个不同的队列中具有可重复性,在时间上具有稳定性,并与不同的长期结局相关。伴有外周疾病表现的 axSpA 亚型与更严重的疾病相关,需要更强化的药物治疗。

临床试验注册

clinicaltrials.gov,临床试验注册编号

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