Two phenothypes of severe asthma identified by cluster analysis

O. Kharevich (Minsk, Belarus), I. Lapteva (Minsk, Belarus), E. Lapteva (Minsk, Belarus)

Source: International Congress 2018 – Clinical markers of asthma
Session: Clinical markers of asthma
Session type: Thematic Poster
Number: 3996
Disease area: Airway diseases

Congress or journal article abstractE-poster

Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
O. Kharevich (Minsk, Belarus), I. Lapteva (Minsk, Belarus), E. Lapteva (Minsk, Belarus). Two phenothypes of severe asthma identified by cluster analysis. 3996

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.


Related content which might interest you:
Identification of asthma phenotypes using cluster analysis
Source: International Congress 2018 – Exploring the importance of daily physical activity in chronic respiratory disease
Year: 2018

Cluster analysis to identify phenotypes in COPD
Source: Annual Congress 2009 - Quality of life and symptoms in COPD
Year: 2009

Cluster analysis and clinical asthma phenotypes
Source: Annual Congress 2013 –Severe asthma: moving from phenotyping to endotyping
Year: 2013


Analysis of phenotypes in a group of severe asthma
Source: International Congress 2019 – Immunopathological mechanisms of lung disease
Year: 2019

Identification of asthma clusters in two independent Korean adult asthma cohorts
Source: Eur Respir J 2013; 41: 1308-1314
Year: 2013



Two novel, severe asthma phenotypes identified during childhood using a clustering approach
Source: Eur Respir J 2012; 40: 55-60
Year: 2012



Identification of clinical phenotypes using cluster analyses in COPD patients
Source: International Congress 2019 – Phenotypes and comorbidities of airway diseases
Year: 2019


Cluster analysis of severe life-threatening asthma: identification of a distinct phenotype characterized by high serum eosinophils
Source: International Congress 2017 – Monitoring asthma control
Year: 2017


Identifying adult asthma phenotypes using a clustering approach
Source: Eur Respir J 2011; 38: 310-317
Year: 2011



Clinical COPD phenotypes identified by cluster analysis: validation with mortality
Source: Eur Respir J 2012; 40: 495-496
Year: 2012


Cluster analysis identifies distinct clinical phenotypes with poor treatment responsiveness in asthma.
Source: International Congress 2018 – Asthma: clinical screening tools
Year: 2018


Phenotypes of adult-onset asthma by cluster analysis
Source: Annual Congress 2012 - Phenotypes and mechanisms of treatment of asthma
Year: 2012

Scores of asthma and asthma severity reveal new regions of linkage in EGEA study families
Source: Eur Respir J 2007; 30: 253-259
Year: 2007



Distinguishing phenotypes of childhood wheeze and cough using latent class analysis
Source: Eur Respir J 2008; 31: 974-981
Year: 2008



Cluster analysis revealed differences on quality of life and susceptibility to exacerbation between subpopulations of smokers including COPD
Source: Annual Congress 2011 - COPD diagnosis
Year: 2011


Defining the clinical clusters of severe asthma within UBIOPRED
Source: International Congress 2015 – Fingerprinting severe asthma
Year: 2015



Urinary metabolomics-profiling of the U-BIOPRED asthma study identified biochemical clusters associated with asthma severity
Source: Virtual Congress 2020 – Phenotypes of obstructive diseases
Year: 2020


Longitudinal validation of clinical COPD phenotypes identified by cluster analysis
Source: Annual Congress 2011 - COPD diagnosis
Year: 2011

Distinct clinical phenotypes of airways disease defined by cluster analysis
Source: Eur Respir J 2009; 34: 812-818
Year: 2009



Latent class analyses used to study phenotypes in severe COPD with exacerbation. A pilot study
Source: Annual Congress 2010 - Epidemiological data for smoking control
Year: 2010