PT  - JOURNAL ARTICLE
AU  - Divo, Miguel
AU  - Casanova, Ciro
AU  - Marin, Jose M.
AU  - Celli, Bartolome
AU  - de Torres, Juan Pablo
AU  - Polverino, Francesca
AU  - Baz, Rebeca
AU  - Cordoba-Lanus, Elizabeth
AU  - Pinto-Plata, Victor
TI  - Identification of clinical phenotypes in patients with and without COPD using cluster analysis
AID  - 10.1183/13993003.congress-2016.PA4613
DP  - 2016 Sep 01
TA  - European Respiratory Journal
PG  - PA4613
VI  - 48
IP  - suppl 60
4099  - http://erj.ersjournals.com/content/48/suppl_60/PA4613.short
4100  - http://erj.ersjournals.com/content/48/suppl_60/PA4613.full
SO  - Eur Respir J2016 Sep 01; 48
AB  - COPD is an heterogeneous disease better characterized by multidimensional phenotyping. Clustering is a technique used to identify discrete subgroups with similar combinations of traits. Except for pulmonary function variables, many other characteristics (6MWT, BMI, QOL) are not unique to COPD.Aim: To compare how discrete clusters form in a mixed cohort of 120 individuals with COPD and controls.Methods: Hundred and twenty patients matched by age and gender were selected, 90 with COPD of which 60 died at 3 years of follow-up. Hierarchical clustering was applied using pulmonary function, functional, anthropometric and QOL variables. Clusters were compared against a selected reference.Results: Four clusters were identified and their composition is shown in A. Cluster 4 composed with 84% controls was used as reference and the comparison and descriptions are shown in B.Conclusion: Clustering is a useful tool to discriminate clinical meaningful phenotypes and by including “controls” we showed that >10% were assigned in COPD predominant clusters. This could be important when designing exploratory studies.