Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema.

ABSTRACT:

Background

There is notable heterogeneity in the clinical presentation of patients with COPD. To characterise this heterogeneity, we sought to identify subgroups of smokers by applying cluster analysis to data from the COPDGene study.

Methods

We applied a clustering method, k-means, to data from 10 192 smokers in the COPDGene study. After splitting the sample into a training and validation set, we evaluated three sets of input features across a range of k (user-specified number of clusters). Stable solutions were tested for association with four COPD-related measures and five genetic variants previously associated with COPD at genome-wide significance. The results were confirmed in the validation set.

Findings

We identified four clusters that can be characterised as (

SUBMITTER: Castaldi PJ 

PROVIDER: S-EPMC4004338 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature