Section of Pulmonary & Critical Care, Department of Medicine, University of Chicago, Chicago, IL.
Division of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of California at Davis, Davis, CA.
Chest. 2018 Feb;153(2):349-360. doi: 10.1016/j.chest.2017.09.026. Epub 2017 Sep 28.
The current interstitial lung disease (ILD) classification has overlapping clinical presentations and outcomes. Cluster analysis modeling is a valuable tool in identifying distinct clinical phenotypes in heterogeneous diseases. However, this approach has yet to be implemented in ILD.
Using cluster analysis, novel ILD phenotypes were identified among subjects from a longitudinal ILD cohort, and outcomes were stratified according to phenotypic clusters compared with subgroups according to current American Thoracic Society/European Respiratory Society ILD classification criteria.
Among subjects with complete data for baseline variables (N = 770), four clusters were identified. Cluster 1 (ie, younger white obese female subjects) had the highest baseline FVC and diffusion capacity of the lung for carbon monoxide (Dlco). Cluster 2 (ie, younger African-American female subjects with elevated antinuclear antibody titers) had the lowest baseline FVC. Cluster 3 (ie, elderly white male smokers with coexistent emphysema) had intermediate FVC and Dlco. Cluster 4 (ie, elderly white male smokers with severe honeycombing) had the lowest baseline Dlco. Compared with classification according to ILD subgroup, stratification according to phenotypic clusters was associated with significant differences in monthly FVC decline (Cluster 4, -0.30% vs Cluster 2, 0.01%; P < .0001). Stratification by using clusters also independently predicted progression-free survival (P < .001) and transplant-free survival (P < .001).
Among adults with diverse chronic ILDs, cluster analysis using baseline characteristics identified four distinct clinical phenotypes that might better predict meaningful clinical outcomes than current ILD diagnostic criteria.
目前的间质性肺疾病（ILD）分类存在重叠的临床表现和结局。聚类分析模型是识别异质性疾病中不同临床表型的一种有价值的工具。然而，这种方法尚未在ILD 中实施。
使用聚类分析，在一个纵向ILD 队列的受试者中确定了新的ILD 表型，并根据表型簇对结果进行分层，与根据当前美国胸科学会/欧洲呼吸学会ILD 分类标准的亚组进行比较。
在有基线变量完整数据的受试者中（N=770），确定了四个簇。簇 1（即年轻的白人肥胖女性受试者）具有最高的基线 FVC 和一氧化碳弥散量（Dlco）。簇 2（即年轻的非裔美国女性受试者，抗核抗体滴度升高）具有最低的基线 FVC。簇 3（即老年白人男性吸烟者，伴有肺气肿共存）具有中等的 FVC 和 Dlco。簇 4（即老年白人男性吸烟者，伴有严重蜂窝肺）具有最低的基线 Dlco。与根据ILD 亚组进行分类相比，根据表型簇进行分层与每月 FVC 下降显著相关（簇 4，-0.30%vs 簇 2，0.01%；P<0.0001）。使用聚类进行分层也独立预测无进展生存率（P<0.001）和无移植生存率（P<0.001）。
在患有不同慢性ILD 的成年人中，使用基线特征的聚类分析确定了四个不同的临床表型，这些表型可能比当前的ILD 诊断标准更好地预测有意义的临床结局。
