Full blood count parameters for the detection of asthma inflammatory phenotypes

Authors

  • X.-Y. Zhang,

    1. Department of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
    2. Graduate School, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
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  • J. L. Simpson,

    1. Priority Research Centre for Asthma and Respiratory Diseases, University of Newcastle, Newcastle, NSW, Australia
    2. Hunter Medical Research Institute, Newcastle, NSW, Australia
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  • H. Powell,

    1. Priority Research Centre for Asthma and Respiratory Diseases, University of Newcastle, Newcastle, NSW, Australia
    2. Hunter Medical Research Institute, Newcastle, NSW, Australia
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  • I. A. Yang,

    1. School of Medicine, The University of Queensland, Brisbane, Qld, Australia
    2. The Prince Charles Hospital, Chermside, Qld, Australia
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  • J. W. Upham,

    1. School of Medicine, The University of Queensland, Brisbane, Qld, Australia
    2. Princess Alexandra Hospital, Brisbane, Qld, Australia
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  • P. N. Reynolds,

    1. Department of Thoracic Medicine, Royal Adelaide Hospital, Adelaide, SA, Australia
    2. Lung Research Laboratory, Hanson Institute, Adelaide, SA, Australia
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  • S. Hodge,

    1. Department of Thoracic Medicine, Royal Adelaide Hospital, Adelaide, SA, Australia
    2. Lung Research Laboratory, Hanson Institute, Adelaide, SA, Australia
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  • A. L. James,

    1. Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, WA, Australia
    2. School of Medicine and Pharmacology, University of Western Australia, Crawley, Perth, WA, Australia
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  • C. Jenkins,

    1. Respiratory Trials, The George Institute for Global Health, Sydney, NSW, Australia
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  • M. J. Peters,

    1. Australian School of Advanced Medicine, Macquarie University, NSW, Australia
    2. Department of Thoracic Medicine, Concord General Hospital, Sydney, NSW, Australia
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  • J.-T. Lin,

    1. Department of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
    2. Graduate School, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China
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  • P. G. Gibson

    Corresponding author
    1. Priority Research Centre for Asthma and Respiratory Diseases, University of Newcastle, Newcastle, NSW, Australia
    2. Hunter Medical Research Institute, Newcastle, NSW, Australia
    3. Department of Respiratory and Sleep Medicine, John Hunter Hospital, New Lambton, NSW, Australia
    4. Woolcock Institute of Medical Research, Sydney, NSW, Australia
    • Correspondence:

      Prof. Peter G. Gibson, Department of Respiratory and Sleep Medicine, John Hunter Hospital, Lookout Road, New Lambton, 2305, NSW, Australia.

      E-mail: Peter.Gibson@hnehealth.nsw.gov.au

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Summary

Background

In asthma, the airway inflammatory phenotype influences clinical characteristics and treatment response. Although induced sputum is the gold standard test for phenotyping asthma, a more accessible method is needed for clinical practice.

Objective

To investigate whether white blood cell counts and/or their derived ratios can predict sputum eosinophils or neutrophils in uncontrolled asthma.

Methods

This cross-sectional study evaluated 164 treated but uncontrolled asthmatic patients with sputum induction and blood collection. Receiver-operating characteristic (ROC) curves were used to assess the relationship between blood and sputum parameters.

Results

There was a significant positive relationship between blood eosinophil parameters and the percentage of sputum eosinophil count. A weak but significant correlation was found between sputum neutrophil percentage and blood neutrophil percentage (r = 0.219, P = 0.005). ROC curve analysis identified that blood eosinophil percentage count was the best predictor for eosinophilic asthma, with an area under the curve (AUC) of 0.907 (P < 0.001). The optimum cut-point for blood eosinophil percentage was 2.7%, and this yielded a sensitivity of 92.2% and a specificity of 75.8%. The absolute blood eosinophil count was also highly predictive with an AUC of 0.898 (P < 0.0001) at a blood eosinophil cut-off of 0.26 × 109/L. The blood eosinophil/lymphocyte ratio (ELR) and eosinophil/neutrophil ratio (ENR) were increased in eosinophilic asthma, and the neutrophil/lymphocyte ratio (NLR) was increased in neutrophilic asthma. Neutrophilic asthma could also be detected by blood neutrophil percentages and NLR, but with less accuracy.

Conclusions and Clinical Relevance

Blood eosinophil counts and derived ratios (ELR and ENR) can accurately predict eosinophilic asthma in patients with persistent uncontrolled asthma despite treatment. Blood neutrophil parameters are poor surrogates for the proportion of sputum neutrophils. Blood counts may be a useful aid in the monitoring of uncontrolled asthma.

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