ArticleBMC pulmonary medicine2017
A cluster analysis of chronic obstructive pulmonary disease in dusty areas cohort identified three subgroups.
Article in BMC pulmonary medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Article
- A machine learning framework for short-term prediction of chronic obstructive pulmonary disease exacerbations using personal air quality monitors and lifestyle data.Scientific reports · 2025Article
- Single cell transcriptomics in blood of patients with chronic obstructive pulmonary disease.BMC pulmonary medicine · 2025Article
- Computational Phenotyping of Obstructive Airway Diseases: A Systematic Review.Journal of asthma and allergy · 2025Review
- Quantitative computed tomography and visual emphysema scores: association with lung function decline.ERJ open research · 2023Article
- Clustering of prostate cancer healthcare pathways in the French National Healthcare database.Cancer innovation · 2023Article
- Telehealth nursing interventions for phenotypes of older adults with COPD: an exploratory study.Frontiers in digital health · 2023Article
- Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers.BMJ open respiratory research · 2022Observational
- Metabolomics Reveals Dysregulated Sphingolipid and Amino Acid Metabolism Associated with Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2022Article
- Unsupervised Clustering Reveals Sarcoidosis Phenotypes Marked by a Reduction in Lymphocytes Relate to Increased Inflammatory Activity on 18FDG-PET/CT.Frontiers in medicine · 2021Article
- Long-term exposure to PMRespiratory research · 2020Article
- Cluster Analysis: A New Approach for Identification of Underlying Risk Factors and Demographic Features of First Trimester Pregnancy Women.Journal of clinical medicine · 2020Article
- Quantitative CT-based structural alterations of segmental airways in cement dust-exposed subjects.Respiratory research · 2020Article
- Different Clusters in Patients with Chronic Obstructive Pulmonary Disease (COPD): A Two-Center Study in Brazil.International journal of chronic obstructive pulmonary disease · 2020Article
- Computed tomography-derived area and density of pectoralis muscle associated disease severity and longitudinal changes in chronic obstructive pulmonary disease: a case control study.Respiratory research · 2019Article
- Correlation between Physical Activity and Lung Function in Dusty Areas: Results from the Chronic Obstructive Pulmonary Disease in Dusty Areas (CODA) Cohort.Tuberculosis and respiratory diseases · 2019Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundChronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable clinical manifestations, structural changes, and treatment responses. In a cohort study, we performed a baseline cluster analysis to identify the subgroups of COPD and to assess the clinical outcomes of each subgroup during a 1-year follow-up.
methodsWe analyzed dusty areas cohort comprising 272 patients with COPD. The main factors with the highest loading in 15 variables were selected using principal component analysis (PCA) at baseline. The COPD patients were classified by hierarchical cluster analysis using clinical, physiological, and imaging data based on PCA-transformed data. The clinical parameters and outcomes during the 1-year follow-up were evaluated among the subgroups.
resultsPCA revealed that six independent components accounted for 77.3% of variance. Three distinct subgroups were identified through the cluster analysis. Subgroup 1 included younger subjects with fewer symptoms and mild airflow obstruction, and they had fewer exacerbations during the 1-year follow-up. Subgroup 2 comprised subjects with additional symptoms and moderate airflow obstruction, and they most frequently experienced exacerbations requiring hospitalization during the 1-year follow-up. Subgroup 3 included subjects with additional symptoms and mild airflow obstruction; this group had more female patients and a modest frequency of exacerbations requiring hospitalization.
conclusionsCluster analysis using the baseline data of a COPD cohort identified three distinct subgroups with different clinical parameters and outcomes. These findings suggest that the identified subgroups represent clinically meaningful subtypes of COPD.
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