Clinical phenotypes of sarcoidosis using cluster analysis: a Spanish population-based cohort study.

IF 3.4 4区 医学 Q2 RHEUMATOLOGY
Raúl Fernández-Ramón, Jorge Javier Gaitán-Valdizán, José Luis Martín-Varillas, Rosalía Demetrio-Pablo, Iván Ferraz-Amaro, Santos Castañeda, Ricardo Blanco
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引用次数: 0

Abstract

Objectives: Sarcoidosis is a clinically heterogenous disease. The objective of this study is the identification of clinical phenotypes using cluster analysis.

Methods: A model-based clustering relaying on 19 clinical variables was performed in a retrospective cohort of 342 sarcoidosis patients, diagnosed and followed-up from 1999 to 2019 in a tertiary hospital at Northern Spain. Chi-square test and ANOVA were used to compare categorical and continuous variables among groups. Two-sample t-tests and the partition of Pearson's chi-square statistic were used in pairwise comparisons. The Wasfi severity score was calculated and compared among clusters.

Results: Cluster analysis identified five groups: C1 (16.1%), C2 (14.3%), C3 (24.3%), C4 (5.0%), and C5 (40.4%). Lung involvement was predominant, ranging from 55.1% (C2) to 100% (C1 and C4). Extrapulmonary involvement was significantly higher in C2 (96.4%) and C3 (98.0%). A significant lower FEV1 percent predicted was detected in C5 (90.5±21.8) versus C1 (102.0±22.9), C3 (102.3±17.6) and C4 (105.8±20.8). The cluster 5 had a lower FVC percent predicted (96.6±18.9) than others, ranging from 108.1±18.0 (C3) to 111.5±21.7 (C4). The prescription of systemic glucocorticoids and non-corticosteroid immunosuppressants was higher in the clusters 1, 3 and 5. Chronicity rates were higher in C3 (31.3%) and C5 (32.6%) compared to C1 (9.1%) and C4 (0%), as well as the Wasfi severity score values.

Conclusions: Five phenotypes with different clinical and prognostic characteristics are proposed in our study. Cluster analysis can be a useful tool for identifying clinical patterns in a disease as heterogeneous as sarcoidosis and optimising its management.

使用聚类分析的肉样瘤病临床表型:一项基于西班牙人群的队列研究。
目的:肉样瘤病是一种临床异质性疾病。本研究的目的是利用聚类分析确定临床表型:方法:对西班牙北部一家三甲医院 1999 年至 2019 年诊断和随访的 342 名肉样瘤病患者进行了基于模型的聚类分析,根据 19 个临床变量进行聚类。采用卡方检验和方差分析比较各组间的分类变量和连续变量。配对比较采用双样本 t 检验和皮尔逊卡方统计分区。计算 Wasfi 严重程度评分并在各组间进行比较:聚类分析确定了五个组别:C1(16.1%)、C2(14.3%)、C3(24.3%)、C4(5.0%)和C5(40.4%)。肺部受累占主导地位,从55.1%(C2)到100%(C1和C4)不等。C2(96.4%)和C3(98.0%)的肺外受累率明显更高。与 C1(102.0±22.9)、C3(102.3±17.6)和 C4(105.8±20.8)相比,C5(90.5±21.8)的 FEV1 预测百分比明显较低。第 5 组的预测 FVC 百分比(96.6±18.9)低于其他组,从 108.1±18.0(C3)到 111.5±21.7(C4)不等。群组 1、3 和 5 中全身使用糖皮质激素和非糖皮质激素免疫抑制剂的比例较高。与C1(9.1%)和C4(0%)以及Wasfi严重程度评分值相比,C3(31.3%)和C5(32.6%)的慢性化率更高:我们的研究提出了具有不同临床和预后特征的五种表型。聚类分析是一种有用的工具,可用于识别肉样瘤病这种异质性疾病的临床模式并优化其治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
18.90%
发文量
377
审稿时长
3-6 weeks
期刊介绍: Clinical and Experimental Rheumatology is a bi-monthly international peer-reviewed journal which has been covering all clinical, experimental and translational aspects of musculoskeletal, arthritic and connective tissue diseases since 1983.
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