Evidence for 2 clusters among patients with noneosinophilic asthma.

BACKGROUND: Although asthma is often seen as an eosinophilic disease associated with atopy, patients with noneosinophilic asthma represent a substantial part of the population with asthma. OBJECTIVE: To apply an unsupervised clustering method in a cohort of 588 patients with noneosinophilic asthma (sputum eosinophils < 3%) recruited from an asthma clinic of a secondary care center. METHODS: Our cluster analysis of the whole cohort identified 2 subgroups as cluster 1 (n = 417) and cluster 2 (n = 171). RESULTS: Cluster 1 comprised a predominantly female group with late disease onset, a low proportion of atopy (24%), and a substantial smoking history (53%). In this cluster, treatment burden was low (<50% of inhaled corticosteroid users); asthma control and quality of life were poor, with median Asthma Control Test, Asthma Control Questionnaire, and Asthma Quality of Life scores of 16, 1.7, and 4.5, respectively, whereas lung function was preserved with a median postbronchodilation forced expiratory volume in 1 second of 93% predicted. Cluster 2 was a predominantly male group, almost exclusively comprising patients with atopy (99%) with early disease onset and a moderate treatment burden (median inhaled corticosteroids dose 800 µg/d equivalent beclomethasone). In cluster 2, asthma was partially controlled, with median Asthma Control Test and Asthma Control Questionnaire scores reaching 18 and 1.3, respectively, and lung function well preserved with a median postbronchodilation of 95% predicted. Although systemic and airway neutrophilic inflammation was the dominant pattern in cluster 1, cluster 2 essentially comprised paucigranulocytic asthma with moderately elevated fraction exhaled nitric oxide. CONCLUSION: Noneosinophilic asthma splits into 2 clusters distinguishing by disease onset, atopic status, smoking history, systemic and airway inflammation, and disease control and quality of life.

Predictors of asthma-related quality of life in a large cohort of asthmatics: A cross-sectional study in a secondary care center.

BACKGROUND: In recent decades, asthma-related quality of life questionnaires have joined objective clinical indicators as important outcome measures. In this study, we sought to investigate the predictors of asthma-related quality of life in a large cohort of patients recruited from a secondary care center. METHODS: We conducted a cross-sectional study on asthmatics (N = 1301) recruited from the Liège University Hospital asthma clinic (Belgium). After performing a descriptive analysis highlighting the distribution of scores from the Mini Asthma Quality of Life Questionnaire (Mini AQLQ) and its four dimensions (symptoms, activity limitation, emotional function, and environmental stimuli), we did multiple regression analysis to identify the independent predictors of AQLQ. RESULTS: Multiple regression beta analysis showed that AQLQ and its four dimensions were primarily associated with asthma control (p < 0.0001 in all instances). Female gender was associated with a lower score for the AQLQ's activity and environmental dimensions (p < 0.05 for both), while current smokers had a higher score on the AQLQ's environmental dimension (p < 0.0001). The burden of asthma treatment was associated with a lower score for the AQLQ's emotional (p < 0.05) and environmental (p < 0.05) dimensions. BMI was associated with a lower score in the AQLQ's activity dimension (p < 0.0001), while the opposite was true for the FeNO test (p < 0.0001). Sputum neutrophils were inversely related to the score for the AQLQ's symptom dimension (p < 0.05), whereas post-bronchodilator FEV1 showed a positive relationship for that same dimension (p < 0.05). CONCLUSION: Asthma control is the main predictor of AQLQ score and impacts all its dimensions, but demographic, functional, and airway inflammatory parameters may also influence some dimensions of the AQLQ.

Comprehensive Cluster Analysis for COPD Including Systemic and Airway Inflammatory Markers.

Chronic obstructive pulmonary disease (COPD) is a complex, multidimensional and heterogeneous disease. The main purpose of the present study was to identify clinical phenotypes through cluster analysis in adults suffering from COPD. A retrospective study was conducted on 178 COPD patients in stable state recruited from ambulatory care at University hospital of Liege. All patients were above 40 years, had a smoking history of more than 20 pack years, post bronchodilator FEV1/FVC <70% and denied any history of asthma before 40 years. In this study, the patients were described by a total of 84 mixed sets of variables with some missing values. Hierarchical clustering on principal components (HCPC) was applied on multiple imputation. In the final step, patients were classified into homogeneous distinct groups by consensus clustering. Three different clusters, which shared similar smoking history were found. Cluster 1 included men with moderate airway obstruction (n = 67) while cluster 2 comprised men who were exacerbation-prone, with severe airflow limitation and intense granulocytic airway and neutrophilic systemic inflammation (n = 56). Cluster 3 essentially included women with moderate airway obstruction (n = 55). All clusters had a low rate of bacterial colonization (5%), a low median FeNO value (<20 ppb) and a very low sensitization rate toward common aeroallergens (0-5%). CAT score did not differ between clusters. Including markers of systemic airway inflammation and atopy and applying a comprehensive cluster analysis we provide here evidence for 3 clusters markedly shaped by sex, airway obstruction and neutrophilic inflammation but not by symptoms and T2 biomarkers.