Individual Respiratory Symptoms and Clinical Outcomes in COPD: Associations with FEV1% and Exacerbation Frequency

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is a progressive and heterogeneous condition characterised by restricted airflow and chronic respiratory symptoms. While composite scores like the COPD Assessment Test (CAT) and St George's Respiratory Questionnaire (SGRQ) are commonly used, the individual impact of respiratory symptoms on clinical outcomes remains unclear. Exploring these relationships is crucial for personalised treatment strategies.

Objective: To explore the association between individual respiratory symptoms and clinical outcomes (FEV1% and exacerbation) in a large international COPD cohort.

Methods: Retrospective cross-sectional analysis of the pooled Collaborative International Assessment (3CIA) dataset comprising data from 22 COPD studies across seven countries (2008–2014). Variables included respiratory symptoms, FEV1%, and annual exacerbation rates. Two-stage multiple linear regression examined symptom-FEV1% associations, with Stage 1 adjusting for age, sex, and BMI, and Stage 2 including all symptoms and clinical covariates. Poisson regression analysed exacerbation counts with similar adjustments.

Results: Women presented higher exacerbation rates despite better lung function than men. Sputum showed the strongest unadjusted association with worse FEV1%, followed by cough and wheeze. However, after covariate adjustment, symptoms lost independent association with FEV1%. For exacerbations, the presence of wheeze (IRR=1.41, p <0.001) and productive symptoms ‘cough and sputum’ (IRR=1.27, p =0.016) remained significant, alongside GOLD severity and mMRC scores.

Conclusion: Individual respiratory symptoms associate with poorer outcomes, but relationships are largely explained by global disease severity for FEV1%. Wheeze and productive symptoms independently predict exacerbation frequency. Findings emphasise multidimensional COPD assessment incorporating comprehensive clinical profiling and symptom evaluation for optimal risk stratification.