ArticleERJ open research2025
Comorbidity profiles in chronic obstructive pulmonary disease: a multicohort study.
Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Estimation of mortality hazard ratios by COPD grade using a systematic review and network meta-analysis: deriving grade-, sex-, and age-specific mortality for a German COPD decision model.Scientific reports · 2026Pooled it
- Clinical comorbidity phenotypes in COPD and their biomarker signatures.ERJ open research · 2026Article
- Exploratory Identification of Multidimensional COPD Clusters Using Unsupervised Analysis.Medicina (Kaunas, Lithuania) · 2026Article
- Biologics in Older Adults with Chronic Obstructive Pulmonary Disease: A Narrative Review.Journal of clinical medicine · 2026Review
- Review
- Coronary heart disease and chronic obstructive pulmonary disease prevalence and temporal trends among United States adults: a national population-based study.Frontiers in epidemiology · 2026Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Comorbidities are common in COPD, adversely affecting patients' health. Cluster analysis has been proposed to study phenotypic variability, but inconsistent results have raised concerns. This study uses uniform machine learning techniques across large COPD cohorts to identify comorbidity clusters. Methods: Cluster analysis was conducted using data from COPD patients from the ECLIPSE study. 13 comorbidities were grouped using hierarchical clustering on self-organising maps to identify dominant subgroups. The analysis was replicated in COPD patients from the Groningen Severe COPD Cohort (GSCC). Results: 2054 of 2164 ECLIPSE participants (1337 (65%) men; mean±sd age 63.3±7.1 years; 22.0% Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage E) with sufficient data were included in the analysis. Four clusters were identified: Musculoskeletal (C1: more females, lower nutritional status), Mental (C2: younger females, highest comorbidity count), Circulatory (C3: more males, older) and Metabolic (C4: older males, high nutritional status). The replication analysis (776 of 1030 GSCC participants; 266 (34.3%) men; mean±sd age 61.4±6.9 years; 58.9% GOLD stage E) confirmed three clusters. Two clusters (C1, C2) showed similar phenotypic signatures to those in ECLIPSE, while the third combined features of C3 and C4. In ECLIPSE, C1 was associated with increased mortality (HR 2.30, 95% CI 1.26-4.13, p=0.006), which was not replicated in GSSC. Conclusion: Comorbidity clusters exist in COPD and are linked to different patient subgroups with varying symptom burden. While cohort-specific variations in disease outcomes were observed, overall, the study's findings support the presence of comorbidity profiles with potential to improve disease management.
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Registered trials
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