Symptom burden and its associations with clinical characteristics in patients with COPD: a clustering approach.

ABSTRACT

Background: Symptom burden in patients with COPD is often under-recognised. In this cross-sectional analysis, we aimed to study the severity of a variety of (non-)respiratory symptoms in patients with and without COPD and to explore the associations between clusters based on symptom severity and other clinical characteristics. Methods: Characteristics were assessed in 538 patients with COPD from primary, secondary and tertiary care and 116 non-COPD participants. The severity of 20 symptoms was measured using a visual analogue scale (VAS), ranging from 0 mm (no symptom) to 100 mm (maximum severity). K-means cluster analysis was applied to symptom severity in the patient sample only. Results: People with COPD were comparable with non-COPD participants in terms of gender (58% versus 55% male, p=0.132) and age (64±9 years versus 63±6 years, p=0.552) and had a reduced forced expiratory volume in 1 s (57±23% predicted versus 111±17% predicted, p<0.001). The COPD group had higher VAS scores for most symptoms (p<0.05). The most severe symptoms in patients with COPD were dyspnoea, fatigue and muscle weakness while non-COPD participants mainly experienced insomnia and micturition. Three clusters were identified in the patient sample. Health status and care dependency differed between all clusters, while functional mobility, exacerbation history and lung function differed between cluster 1 and the other two clusters (p<0.05). Conclusions: People with COPD report a high burden of respiratory as well as non-respiratory symptoms. Cluster analysis demonstrated a co-occurrence of different levels of symptom severity, highlighting the heterogeneity of symptoms experience. Identifying clusters of patients with shared symptom experiences will help us to understand the impact of the disease and define integrated, multidimensional treatment strategies.