ArticleBMC pulmonary medicine2016
Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters.
Article in BMC pulmonary medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Development and initial validation of the Asthma Severity Scoring System (ASSESS).The Journal of allergy and clinical immunology · 2020Trial
- A Case Report of Refractory Allergic Bronchopulmonary Aspergillosis: The Art of Selection, Discontinuation and Switching Biologics.Journal of inflammation research · 2026Article
- Asthma Phenotypes and Biomarkers.Respiratory care · 2025Review
- Computational Phenotyping of Obstructive Airway Diseases: A Systematic Review.Journal of asthma and allergy · 2025Review
- Real-World Biologic Use Patterns in Severe Asthma, 2015-2021: The CLEAR Study.Pragmatic and observational research · 2025Article
- Secondary Non-Response to Biologic Treatment in Patients with Severe Asthma.Journal of asthma and allergy · 2025Article
- Leukocyte redistribution as immunological biomarker of corticosteroid resistance in severe asthma.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2022Article
- Asthma clustering methods: a literature-informed application to the children's health study data.The Journal of asthma : official journal of the Association for the Care of Asthma · 2022Review
- Physical Activity and Its Association with Traditional Outcome Measures in Pulmonary Arterial Hypertension.Annals of the American Thoracic Society · 2022Article
- Asthma with Fixed Airflow Obstruction: From Fixed to Personalized Approach.Journal of personalized medicine · 2022Review
- Biomarkers in Different Asthma Phenotypes.Genes · 2021Review
- A Systematic Review of Asthma Phenotypes Derived by Data-Driven Methods.Diagnostics (Basel, Switzerland) · 2021Review
- Mixed Sputum Granulocyte Longitudinal Impact on Lung Function in the Severe Asthma Research Program.American journal of respiratory and critical care medicine · 2021Article
- Instability of sputum molecular phenotypes in U-BIOPRED severe asthma.The European respiratory journal · 2021Article
- Stability of peripheral blood immune markers in patients with asthma.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2019Article
- Reconceptualizing developmental language disorder as a spectrum disorder: issues and evidence.International journal of language & communication disorders · 2019Article
- A retrospective observational study on pheno-endotypes of severe asthma among adults attending asthma clinic in a tertiary care centre in India.Lung India : official organ of Indian Chest SocietyArticle
- Severe Asthma Phenotypes - How Should They Guide Evaluation and Treatment?The journal of allergy and clinical immunology. In practiceReview
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8 authors.
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Abstract
backgroundAlthough the heterogeneous nature of asthma has prompted asthma phenotyping with physiological or biomarker data, these studies have been mostly cross-sectional. Longitudinal studies that assess the stability of phenotypes based on a combination of physiological, clinical and biomarker data are currently lacking. Our objective was to assess the longitudinal stability of clusters derived from repeated measures of airway and physiological data over a 1-year period in moderate and severe asthmatics.
methodsA total of 125 subjects, 48 with moderate asthma (MA) and 77 with severe asthma (SA) were evaluated every 3 months and monthly, respectively, over a 1-year period. At each 3-month time point, subjects were grouped into 4 asthma clusters (A, B, C, D) based on a combination of clinical (duration of asthma), physiological (FEV1 and BMI) and biomarker (sputum eosinophil count) variables, using k-means clustering.
resultsMajority of subjects in clusters A and C had severe asthma (93 % of subjects in cluster A and 79.5 % of subjects in cluster C at baseline). Overall, a total of 59 subjects (47 %) had stable cluster membership, remaining in clusters with the same subjects at each evaluation time. Cluster A was the least stable (21 % stability) and cluster B was the most stable cluster (71 % stability). Cluster stability was not influenced by changes in the dosage of inhaled corticosteroids.
conclusionAsthma phenotyping based on clinical, physiologic and biomarker data identified clusters with significant differences in longitudinal stability over a 1-year period. This finding indicates that the majority of patients within stable clusters can be phenotyped with reasonable accuracy after a single measurement of lung function and sputum eosinophilia, while patients in unstable clusters will require more frequent evaluation of these variables to be properly characterized.
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