Prediction of first acute exacerbation using COPD subtypes identified by cluster analysis

Abstract

Purpose

In patients with COPD, acute exacerbation (AE) is not only an important determinant of prognosis, but also an important factor in choosing therapeutic agents. In this study, we evaluated the usefulness of COPD subtypes identified through cluster analysis to predict the first AE.

Patients and methods

Among COPD patients in the Korea COPD Subgroup Study (KOCOSS) cohort, 1,195 who had follow-up data for AE were included in our study. We selected seven variables for cluster analysis – age, body mass index, smoking status, history of asthma, COPD assessment test (CAT) score, post-bronchodilator (BD) FEV ₁ % predicted, and diffusing capacity of carbon monoxide % predicted.

Results

K-means clustering identified four clusters for COPD that we named putative asthma-COPD overlap (ACO), mild COPD, moderate COPD, and severe COPD subtypes. The ACO group (n=196) showed the second-best post-BD FEV ₁ (75.5% vs 80.9% [mild COPD, n=313] vs 52.4% [moderate COPD, n=345] vs 46.7% [severe COPD, n=341] predicted), the longest 6-min walking distance (424 m vs 405 m vs 389  m vs 365 m), and the lowest CAT score (12.2 vs 13.7 vs 15.6 vs 17.5) among the four groups. ACO group had greater risk for first AE compared to the mild COPD group (HR, 1.683; 95% CI, 1.175–2.410). The moderate COPD and severe COPD group HR values were 1.587 (95% CI, 1.145–2.200) and 1.664 (95% CI, 1.203–2.302), respectively. In addition, St. George’s Respiratory Questionnaire score (HR: 1.019; 95% CI, 1.014–1.024) and gastroesophageal reflux disease were independent factors associated with the first AE (HR: 1.535; 95% CI, 1.116–2.112).

Conclusion

Our cluster analysis revealed an exacerbator subtype of COPD independent of FEV ₁. Since these patients are susceptible to AE, a more aggressive treatment strategy is needed in these patients.