Chronic Obstructive Pulmonary Disease Subtypes. Transitions over Time

Abstract

Background: Although subtypes of chronic obstructive pulmonary disease are recognized, it is unknown what happens to these subtypes over time. Our objectives were to assess the stability of cluster-based subtypes in patients with stable disease and explore changes in clusters over 1 year.

Methods: Multiple correspondence and cluster analysis were used to evaluate data collected from 543 stable patients included consecutively from 5 respiratory outpatient clinics.

Results: Four subtypes were identified. Three of them, A, B, and C, had marked respiratory profiles with a continuum in severity of several variables, while the fourth, subtype D, had a more systemic profile with intermediate respiratory disease severity. Subtype A was associated with less dyspnea, better health-related quality of life and lower Charlson comorbidity scores, and subtype C with the most severe dyspnea, and poorer pulmonary function and quality of life, while subtype B was between subtypes A and C. Subtype D had higher rates of hospitalization the previous year, and comorbidities. After 1 year, all clusters remained stable. Generally, patients continued in the same subtype but 28% migrated to another cluster. Together with movement across clusters, patients showed changes in certain characteristics (especially exercise capacity, some variables of pulmonary function and physical activity) and changes in outcomes (quality of life, hospitalization and mortality) depending on the new cluster they belonged to.

Conclusions: Chronic obstructive pulmonary disease clusters remained stable over 1 year. Most patients stayed in their initial subtype cluster, but some moved to another subtype and accordingly had different outcomes.

Fig 1. Map of clusters and distribution of patients.

Map created by the first and second components derived from the MCA is shown at the center. Four circles at the sides show how patients move between clusters after one year of follow-up. Relative positions of the subjects in the planes are represented by different colors, depending on the subtype provided by the cluster analysis. Definition of the axes is suggested based on information provided in appendix Table A1. The horizontal axis, first component, can be defined as an index of the respiratory conditions of the patient, milder (left side) vs. more severe (right side). The vertical axis, second component, can be defined as an index of the systemic status, worse (bottom) vs. better (top).

Fig 2. Partial dendrogram obtained from the cluster analysis.

The dendogram represents the results from the cluster analysis performed with the four components obtained from the multiple correspondence analysis. The graphical display includes an easy interpretation of the partition and a brief description of the resulting clusters.

Fig 3. Kaplan-Meier estimate of the survival function during the one year period of follow-up stratified by cluster.

Log-rank test for homogeneity (p < 0.001). Significant differences adjusted for multiple comparisons (Bonferroni) were observed between clusters A and C; A and D; and B and D.