Cluster analysis and clinical asthma phenotypes.
Cluster analysis and clinical asthma phenotypes.
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DOI：
10.1164/rccm.200711-1754oc
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发表时间：
2008-08-01
影响因子：
24.7
通讯作者：
Green RH
中科院分区：
文献类型：
--
作者：
Haldar P;Pavord ID;Shaw DE;Berry MA;Thomas M;Brightling CE;Wardlaw AJ;Green RH
哮喘表达的异质性是多维的，包括临床、生理和病理参数的变异性。分类需要在统一的模型中考虑这些不同的领域。探索多变量数学技术--k-均值聚类分析在识别不同表型群中的应用。我们对三个独立的哮喘人群进行了k-均值聚类分析。将以轻到中度疾病为主的初级保健(n=184)人群与二级保健(n=187)管理的难治性哮喘人群进行比较。然后，我们比较了以难治性哮喘为主的第三组68名受试者在哮喘结果(恶化频率和12个月时皮质类固醇剂量变化)方面的差异，这些受试者在进入一项随机试验时聚集在一起，比较了最小化嗜酸性炎症策略(炎症引导策略)和标准治疗策略的差异。两组(早发性特应性和肥胖性，非嗜酸性粒细胞)在两个哮喘人群中都是常见的。症状表现与嗜酸性气道炎(早发症状为主，晚发炎症为主)明显不一致的两个簇是难治性哮喘所特有的。炎症引导治疗对两个不协调的亚组均有优势，导致炎症主导组的恶化频率降低(3.53SD1.18比0.38SD0.13)，症状主导组的吸入皮质类固醇剂量减少(平均差异为1,829μg倍氯米松当量/d[95%可信区间，307-3,349μg]；P=0.02)。聚类分析提供了一种新的多维方法来识别哮喘表型，这些表型在临床上对治疗算法的反应存在差异。
Heterogeneity in asthma expression is multidimensional, including variability in clinical, physiologic, and pathologic parameters. Classification requires consideration of these disparate domains in a unified model. To explore the application of a multivariate mathematical technique, k-means cluster analysis, for identifying distinct phenotypic groups. We performed k-means cluster analysis in three independent asthma populations. Clusters of a population managed in primary care (n = 184) with predominantly mild to moderate disease, were compared with a refractory asthma population managed in secondary care (n = 187). We then compared differences in asthma outcomes (exacerbation frequency and change in corticosteroid dose at 12 mo) between clusters in a third population of 68 subjects with predominantly refractory asthma, clustered at entry into a randomized trial comparing a strategy of minimizing eosinophilic inflammation (inflammation-guided strategy) with standard care. Two clusters (early-onset atopic and obese, noneosinophilic) were common to both asthma populations. Two clusters characterized by marked discordance between symptom expression and eosinophilic airway inflammation (early-onset symptom predominant and late-onset inflammation predominant) were specific to refractory asthma. Inflammation-guided management was superior for both discordant subgroups leading to a reduction in exacerbation frequency in the inflammation-predominant cluster (3.53 [SD, 1.18] vs. 0.38 [SD, 0.13] exacerbation/patient/yr, P = 0.002) and a dose reduction of inhaled corticosteroid in the symptom-predominant cluster (mean difference, 1,829 μg beclomethasone equivalent/d [95% confidence interval, 307–3,349 μg]; P = 0.02). Cluster analysis offers a novel multidimensional approach for identifying asthma phenotypes that exhibit differences in clinical response to treatment algorithms.