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Different Clusters in Patients with Chronic Obstructive Pulmonary Disease (COPD): A Two-Center Study in Brazil

Authors Zucchi JW, Franco EAT, Schreck T, Castro e Silva MH, Migliorini SRDS, Garcia T, Mota GAF, de Morais BEB, Machado LHS, Batista ANR, de Paiva SAR, de Godoy I, Tanni SE

Received 24 June 2020

Accepted for publication 6 September 2020

Published 6 November 2020 Volume 2020:15 Pages 2847—2856

DOI https://doi.org/10.2147/COPD.S268332

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Richard Russell


José William Zucchi,1 Estefânia Aparecida Thomé Franco,1 Thomas Schreck,2 Maria Helena Castro e Silva,3 Sandro Rogerio dos Santos Migliorini,3 Thaís Garcia,1 Gustavo Augusto Ferreira Mota,1 Bruna Evelyn Bueno de Morais,1 Luiz Henrique Soares Machado,1 Ana Natália Ribeiro Batista,1 Sergio Alberto Rupp de Paiva,1 Irma de Godoy,1 Suzana Erico Tanni1

1Pulmonology Division of Botucatu Medical School, São Paulo State University (UNESP), Botucatu, Brazil; 2Ostbayerische Technische Hochschule Regensburg (OTH Regensburg), Faculty of Business Studies, Regensburg, German; 3Pulmonology Division of Federal University of Triângulo Mineiro, Uberaba, Brazil

Correspondence: José William Zucchi Email jwzucchi@hotmail.com

Background: Chronic obstructive pulmonary disease (COPD) has a functional definition. However, differences in clinical characteristics and systemic manifestations make COPD a heterogeneous disease and some manifestations have been associated with different risks of acute exacerbations, hospitalizations, and death.
Objective: Therefore, the objective of the study was to evaluate possible clinical clusters in COPD at two study centers in Brazil and identify the associated exacerbation and mortality rate during 1 year of follow-up.
Methods: We included patients with COPD and all underwent an evaluation composed of the Charlson Index, body mass index (BMI), current pharmacological treatment, smoking history (packs-year), history of exacerbations/hospitalizations in the last year, spirometry, six-minute walking test (6MWT), quality of life questionnaires, dyspnea, and hospital anxiety and depression scale. Blood samples were also collected for measurements of C-reactive protein (CRP), blood gases, laboratory analysis, and blood count. For the construction of the clusters, 13 continuous variables of clinical importance were considered: hematocrit, CRP, triglycerides, low density lipoprotein, absolute number of peripheral eosinophils, age, pulse oximetry, BMI, forced expiratory volume in the first second, dyspnea, 6MWD, total score of the Saint George Respiratory Questionnaire and packs-year of smoking. We used the Ward and K-means methods and determined the best silhouette value to identify similarities of individuals within the cluster (cohesion) in relation to the other clusters (separation). The number of clusters was determined by the heterogeneity values of the cluster, which in this case was determined as four clusters.
Results: We evaluated 301 COPD patients and identified four different groups of COPD patients. The first cluster (203 patients) was characterized by fewer symptoms and lower functional severity of the disease, the second cluster by higher values of peripheral eosinophils, the third cluster by more systemic inflammation and the fourth cluster by greater obstructive severity and worse gas exchange. Cluster 2 had an average of 959± 3 peripheral eosinophils, cluster 3 had a higher prevalence of nutritional depletion (46.1%), and cluster 4 had a higher BODE index. Regarding the associated comorbidities, we found that only obstructive sleep apnea syndrome and pulmonary thromboembolism were more prevalent in cluster 4. Almost 50% of all patients presented an exacerbation during 1 year of follow-up. However, it was higher in cluster 4, with 65% of all patients having at least one exacerbation. The mortality rate was statistically higher in cluster 4, with 26.9%, vs 9.6% in cluster 1.
Conclusion: We could identify four clinical different clusters in these COPD populations, that were related to different clinical manifestations, comorbidities, exacerbation, and mortality rate. We also identified a specific cluster with higher values of peripheral eosinophils.

Keywords: COPD, eosinophils, cluster analysis, COPD phenotype, lung function

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