Clinical ACO phenotypes: Description of a heterogeneous entity

Abstract

Background: Because ACO (Asthma-COPD-Overlap) does not fill out asthma or COPD (Chronic Obstructive Pulmonary Disease) criteria, such patients are poorly evaluated. The aim of this study was to screen asthma and COPD for an alternative diagnosis of ACO, then to determine subgroups of patients, using cluster analysis.

Material and methods: Using GINA-GOLD stepwise approach, asthmatics and COPD were screened for ACO. Clusterization was then performed employing Multiple Correspondent Analysis (MCA) model, encompassing 9 variables (age, symptoms onset, sex, BMI (Body Mass Index), smoking, FEV-1, dyspnea, exacerbation, comorbidity). Finally, clusters were compared to determine phenotypes.

Results: MCA analysis was performed on 172 ACO subjects. To better distinguish clusters, the analysis was then focused on 55 subjects, having at least one cosine squared >0.3. Six clusters were identified, allowing the description of 4 phenotypes. Phenotype A represented overweighed heavy smokers, with an early onset and a severe disease (27% of ACO patients). Phenotype B gathered similar patients, with a late onset (29%). Patients from Phenotypes C-D were slighter smokers, presenting a moderate disease, with early and late onset respectively (respectively 13% and 31%).

Conclusions: By providing evidences for clusters within ACO, our study confirms its heterogeneity, allowing the identification of 4 phenotypes. Further prospective studies are mandatory to confirm these data, to determine both specific management requirements and prognostic value.

Keywords: ACO; Asthma; COPD; Cluster; Heterogeneity; MCA; Phenotype.

Fig. 1

Representation of the 9 categorical variables using Multiple Component Analysis. Categorical variables are represented by diamonds. Grey diamonds represent variables with low values of square cosines, and black diamonds represent variables with high values of square cosines. BMI: Body Mass Index; mMRC: modified Medical Research Council; PY: pack year; FEV-1: Forced Expiratory Volume in 1 second; < 62 yo: age inferior to 62 years old; ≥62 yo: minimum age of 62 years old; < 40 yo: Onset of respiratory symptoms before 40 years old; ≥ 40 yo: Onset of respiratory symptoms from 40 year olds; < 30 PY: tobacco consumption inferior to 30 pack-year; ≥ 30 PY: tobacco consumption of at least 30 pack year; < 2 EPY: less than 2 exacerbations per year; ≥ 2 EPY: at least 2 exacerbations per year; cm < 2: less than 2 comorbidities; cm ≥ 2: at least 2 comorbidities.

Fig. 2

Visual representation of clustering analysis. mMRC: modified Medical Research Council; PY: pack year; FEV-1: Forced Expiratory Volume in 1 second; 55 ACO patients are represented on the two-dimensional graph. Dots were gathered together if close enough, creating 6 ellipses which represent 6 clusters of patients. After comparing clusters with the whole collected data, clusters determined different phenotypes different in term of age, age of onset of respiratory symptoms, dyspnea (mMRC), FEV-1 (% of predicted value), oxygen saturation (sat), smoking history (PY: pack year), BMI (Body Mass Index), number of comorbidity, frequency of mood disorder and LAMA (long acting muscarinic antagonist) prescription.

Fig. 3

Final phenotypic expression of ACO patients. mMRC: modified Medical Research Council; PY: pack year; FEV-1: Forced Expiratory Volume in 1 second; cm < 2: less than 2 comorbidities; cm ≥ 2: at least 2 comorbidities; BMI: Body Mass Index; ≤ 30 PY: tobacco consumption inferior to 30 pack-year; > 30 PY: tobacco consumption of at least 30 pack year.