基于聚类分析对慢性肺部疾病表型的研究进展

慢性肺部疾病包括慢性阻塞性肺疾病（COPD）、支气管哮喘、支气管扩张、间质性肺病、肺结节病、尘病和慢性肺曲霉菌病等。这些疾病具有不同的临床表型，同一治疗方案对不同表型的疗效可能存在很大区别，因此准确分析表型对制定个体化治疗方案意义重大。聚类分析是依据研究对象距离远近与相似程度的差异，将它们分成不同亚型的统计学方法。近年来，学术界发现聚类分析可用于包括慢性肺部疾病在内多种疾病的表型研究。本文对慢性肺部疾病表型的聚类分析研究作一综述，总结出该类疾病表型研究的进展和聚类分析的常用研究策略。

Advances in Research on Phenotypes of Chronic Lung Diseases Based on Cluster Analysis

Chronic lung diseases include chronic obstructive pulmonary disease (COPD), bronchial asthma, bronchiectasis, interstitial lung disease, pulmonary sarcoidosis, dust disease, and chronic pulmonary aspergillosis. These diseases have different clinical phenotypes, and the efficacy of the same treatment regimen for different phenotypes may vary greatly, so accurate analysis of the phenotype is of great significance for the development of individualized treatment options. Cluster analysis is based on the differences in distance and similarity of the subjects, and they are divided into statistical methods of different subtypes. In recent years, academic circles have found that cluster analysis can be used for phenotypic studies of a variety of diseases including chronic lung diseases. This article reviews the cluster analysis of chronic lung disease phenotypes, and summarizes the progress of phenotypic research and the commonly used research strategies for cluster analysis.