Predictors of sputum and BAL eosinophilia in the Wessex Severe Asthma Cohort
Predictors of sputum and BAL eosinophilia in the Wessex Severe Asthma Cohort
Background: In severe asthma, the presence of airway eosinophilia is a key “treatable trait”. Airway eosinophilia may be proximal or distal, however work on predictors of airway eosinophilia have focussed on the proximal compartment which is less invasive to sample.
The Wessex Severe Asthma Cohort (WSAC) included 342 severe asthmatics for detailed phenotyping, including bronchoalveolar lavage (BAL) and sputum induction in some participants. We aimed to use data from WSAC to determine the most accurate non-invasive predictor of eosinophilia in participants with severe asthma.
Method: Severe asthmatics in WSAC were included if they underwent BAL or successful sputum induction. The value of Fraction of Exhaled Nitric Oxide (FeNO), blood eosinophil count and periostin in predicting sputum or BAL eosinophilia (3% or 1% respectively) were assessed using Receiver Operating Characteristic (ROC) curves.
Results: All three measures were more accurate at predicting BAL than sputum eosinophilia. FeNO demonstrated a higher predictive value than the other measures in both compartments. Optimal thresholds were similar across compartments for FeNO but more divergent for periostin and blood.
Conclusion: Within this cohort, FeNO was the strongest predictor of sputum or BAL eosinophilia. All factors assessed were stronger at predicting BAL eosinophilia than sputum.
Jones, Thomas
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Brown, Thomas
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Elliott, Scott
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Barber, Clair
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Gove, Kerry
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Lau, Laurie
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Rupani, Hitasha
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Chauhan, Anoop
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Howarth, Peter
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Ono, Junya
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Izuhara, Kenji
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September 2017
Jones, Thomas
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Brown, Thomas
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Elliott, Scott
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Barber, Clair
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Gove, Kerry
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Lau, Laurie
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Rupani, Hitasha
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Chauhan, Anoop
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Howarth, Peter
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Ono, Junya
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Izuhara, Kenji
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Jones, Thomas, Brown, Thomas, Elliott, Scott, Barber, Clair, Gove, Kerry, Lau, Laurie, Rupani, Hitasha, Chauhan, Anoop, Howarth, Peter, Ono, Junya and Izuhara, Kenji
(2017)
Predictors of sputum and BAL eosinophilia in the Wessex Severe Asthma Cohort.
European Respiratory Journal, 50 (Suppl 61), [PA4765].
Record type:
Meeting abstract
Abstract
Background: In severe asthma, the presence of airway eosinophilia is a key “treatable trait”. Airway eosinophilia may be proximal or distal, however work on predictors of airway eosinophilia have focussed on the proximal compartment which is less invasive to sample.
The Wessex Severe Asthma Cohort (WSAC) included 342 severe asthmatics for detailed phenotyping, including bronchoalveolar lavage (BAL) and sputum induction in some participants. We aimed to use data from WSAC to determine the most accurate non-invasive predictor of eosinophilia in participants with severe asthma.
Method: Severe asthmatics in WSAC were included if they underwent BAL or successful sputum induction. The value of Fraction of Exhaled Nitric Oxide (FeNO), blood eosinophil count and periostin in predicting sputum or BAL eosinophilia (3% or 1% respectively) were assessed using Receiver Operating Characteristic (ROC) curves.
Results: All three measures were more accurate at predicting BAL than sputum eosinophilia. FeNO demonstrated a higher predictive value than the other measures in both compartments. Optimal thresholds were similar across compartments for FeNO but more divergent for periostin and blood.
Conclusion: Within this cohort, FeNO was the strongest predictor of sputum or BAL eosinophilia. All factors assessed were stronger at predicting BAL eosinophilia than sputum.
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Published date: September 2017
Venue - Dates:
European Respiratory Society International Congress, , Milan, Italy, 2017-09-09 - 2017-09-13
Identifiers
Local EPrints ID: 422514
URI: http://eprints.soton.ac.uk/id/eprint/422514
ISSN: 0903-1936
PURE UUID: 3b119b11-1276-4ca6-bac3-045eb061292a
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Date deposited: 25 Jul 2018 16:30
Last modified: 15 Mar 2024 21:00
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Contributors
Author:
Thomas Jones
Author:
Thomas Brown
Author:
Scott Elliott
Author:
Clair Barber
Author:
Kerry Gove
Author:
Laurie Lau
Author:
Hitasha Rupani
Author:
Anoop Chauhan
Author:
Junya Ono
Author:
Kenji Izuhara
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