Clinical ACO phenotypes: Description of a heterogeneous entity

Area of Science:

• Pulmonology
• Data Science
• Clinical Medicine

Background:

• Asthma-COPD-Overlap (ACO) diagnosis is challenging as patients often don't meet criteria for either asthma or Chronic Obstructive Pulmonary Disease (COPD).
• This necessitates a refined approach to evaluate and classify patients presenting with overlapping respiratory symptoms.
• The study aimed to screen for ACO and identify distinct patient subgroups using cluster analysis.

Observation:

• A stepwise approach based on GINA and GOLD guidelines was used to screen for ACO.
• Multiple Correspondence Analysis (MCA) was employed, analyzing nine variables including age, symptom onset, BMI, smoking status, FEV-1, dyspnea, exacerbations, and comorbidities.
• Initial analysis included 172 ACO subjects, with a focus on 55 subjects for refined cluster distinction.

Findings:

• Six clusters were identified, leading to the definition of four distinct ACO phenotypes.
• Phenotype A (27%): Overweight, heavy smokers, early onset, severe disease.
• Phenotypes B (29%), C (13%), and D (31%) represented variations in onset, smoking intensity, and disease severity.

Implications:

• The findings confirm the significant heterogeneity within the ACO population.
• Identification of these phenotypes provides a basis for potentially tailored management strategies.
• Further prospective studies are required to validate these phenotypes and assess their prognostic value and specific treatment needs.