系统聚类与两步聚类分析对有症状气道疾病患者的表型研究

Study of the clinical phenotype of symptomatic chronic airways disease by hierarchical cluster analysis and two-step cluster analyses

目的 采用系统聚类和两步聚类分析研究具有喘息症状的慢性气道疾病患者的临床表型.方法 选2012年4月至2015年1月北京市东城区东华门社区和海淀区清河社区居民,过去1年内曾出现喘息症状的患者121例,收集问卷调查、肺功能、血清总IgE水平、血嗜酸性粒细胞计数及呼气峰流量（PEF）等资料.选9个变量,吸入沙丁胺醇前第1秒用力呼气容积（FEV1）/用力肺活量（FVC）×100％、吸入沙丁胺醇前FEV1占预计值百分比、吸入沙丁胺醇后FEV1改善率、残气量（RV）占预计值百分比、一氧化碳弥散系数占预计值百分比、PEF变异率、血清总IgE水平、累计吸烟量（包年）、呼吸道症状（咳嗽、咳痰）.采用系统聚类和两步聚类分析进行表型归类.结果 （1）通过系统聚类分析法将患者分为4类,4类患者在吸入沙丁胺醇前（FEVl/ FVC）×100％和FEV1占预计值百分比、吸入沙丁胺醇后FEV1改善率、最大呼气中段流量（MMEF）占预计值百分比、一氧化碳弥散系数占预计值百分比、RV占预计值百分比、血清总IgE水平、累计吸烟量、圣乔治呼吸问卷（SGRQ）评分、1年内急性加重情况、PEF变异率、过敏性皮炎差异有统计学意义（P＜0.05）.（2）两步聚类分析法将患者分为4类,4类患者在性别分布、呼吸道症状、吸入沙丁胺醇前（FEV1/FVC）×100％和FEV1占预计值百分比、吸入沙丁胺醇后FEV1改善率、MMEF占预计值百分比、一氧化碳弥散系数占预计值百分比、RV占预计值百分比、PEF变异率、血清总IgE水平、累计吸烟量、SGRQ评分差异有统计学意义（P＜0.05）.结论 不同聚类分析法可将具有喘息症状的慢性气道疾病患者分为不同的临床表型,表型的划分有助于指导该类患者的个体化治疗.

Objective To study the distinct clinical phenotype of chronic airway diseases by hierarchical cluster analysis and two-step cluster analysis.Methods A population sample of adult patients in Donghuamen community,Dongcheng district and Qinghe community,Haidian district,Beijing from April 2012 to January 2015,who had wheeze within the last 12 months,underwent detailed investigation,including a clinical questionnaire,pulmonary function tests,total serum IgE levels,blood eosinophil level and a peak flow diary.Nine variables were chosen as evaluating parameters,including pre-salbutamol forced expired volume in one second（FEV1）/forced vital capacity （FVC） ratio,pre-salbutamol FEV1,percentage of post-salbutamol change in FEV1,residual capacity,diffusing capacity of the lung for carbon monoxide/alveolar volume adjusted for haemoglobin level,peak expiratory flow （PEF） variability,serum IgE level,cumulative tobacco cigarette consumption （pack-years） and respiratory symptoms （cough and expectoration）.Subjects＇ different clinical phenotype by hierarchical cluster analysis and two-step cluster analysis was identified.Results （1） Four clusters were identified by hierarchical cluster analysis.Cluster 1 was chronic bronchitis in smokers with normal pulmonary function.Cluster 2 was chronic bronchitis or mild chronic obstructive pulmonary disease （COPD） patients with mild airflow limitation.Cluster 3 included COPD patients with heavy smoking,poor quality of life and severe airflow limitation.Cluster 4 recognized atopic patients with mild airflow limitation,elevated serum IgE and clinical features of asthma.Significant differences were revealed regarding pre-salbutamol FEV1/FVC%,pre-salbutamol FEV1% pred,postsalbutamol change in FEV1 %,maximal mid-expiratory flow curve （MMEF）% pred,carbon monoxide diffusing capacity per liter of alveolar（DLCO）/（VA）% pred,residual volume（RV）% pred,total serum IgE level,smoking history （pack-years）,St.George＇ s respiratory questionnaire （SGRQ） score,acute exacerbation in the past one year,PEF variability and allergic dermatitis （P 〈 0.05）.（2） Four clusters were also identified by two-step cluster analysis as followings,cluster 1,COPD patients with moderate to severe airflow limitation;cluster 2,asthma and COPD patients with heavy smoking,airflow limitation and increased airways reversibility;cluster 3,patients having less smoking and normal pulmonary function with wheezing but no chronic cough;cluster 4,chronic bronchitis patients with normal pulmonary function and chronic cough.Significant differences were revealed regarding gender distribution,respiratory symptoms,pre-salbutamol FEV1/FVC%,pre-salbutamol FEV1 % pred,post-salbutamol change in FEV1 %,MMEF% pred,DLCO/VA% pred,RV% pred,PEF variability,total serum IgE level,cumulative tobacco cigarette consumption （pack-years）,and SGRQ score （P 〈 0.05）.Conclusion By different cluster analyses,distinct clinical phenotypes of chronic airway diseases are identified.Thus,individualized treatments may guide doctors to provide based on different phenotypes.