Stratifying COPD patients by cluster analysis using clinical and behavioral variables

Introduction: The FEV1 GOLD criteria are widely used to classify severity of airflow obstruction. GOLD 2020 emphasizes that there is only a weak correlation between FEV1, symptoms and impairment of patient’s health status. Various studies aimed to identify COPD phenotypes by cluster analyses, but did not include behavioral variables. Aims and Objectives: The aim of the study was to identify the four COPD phenotypes of Burgel PR et al. ERJ. 2010; 36: 531-539 in a COPD cohort and to add behavioral variables. Methods: First, we used real-life clinical data of a COPD cohort (n=122) to replicate the phenotypes of Burgel by hierarchical cluster analysis. Second, additional variables were included in this analysis: airtrapping, coping, QoL and physical activity. Results: When using essentially the same variables, we could not replicate Burgel’s clusters. In contrast to Burgel, our clusters mainly differed on age, packyears, BMI and depression scale. Adding the four new types of variables led to the formation of two clusters that mainly differed from each other in the number of steps per day (8260 [6747-9773] vs. 3663[2573-4699]), health related quality of life (4[3-6] vs. 6[4-7]), limitations in general (11[7-15] vs. 15[10-18]), limitations during house hold (10[3-23] vs. 17[7-24]) and shortness of breath (9[5-15] vs. 13[10-16]). Conclusions: We were not able to replicate the reported clusters of Burgel. Adding behavior parameters (physical activity, coping and QoL) leads to new clusters that differ more on these than on clinical parameters. The heterogeneity in the COPD population implies personalized treatment and tailored strategy instead of stratifying COPD patients in subgroups.