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Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice

Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice
Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice
Purpose: Acute, severe asthma exacerbations can be difficult to predict and thus prevent. Patients who have frequent exacerbations are of particular concern. Practical exacerbation predictors are needed for these patients in the primary-care setting.

Patients and methods: Medical records of 130,547 asthma patients aged 12–80 years from the UK Optimum Patient Care Research Database and Clinical Practice Research Datalink, 1990–2013, were examined for 1 year before (baseline) and 1 year after (outcome) their most recent blood eosinophil count. Baseline variables predictive (P<0.05) of exacerbation in the outcome year were compared between patients who had two or more exacerbations and those who had no exacerbation or only one exacerbation, using uni- and multivariable logistic regression models. Exacerbation was defined as asthma-related hospital attendance/admission (emergency or inpatient) or acute oral corticosteroid (OCS) course.

Results: Blood eosinophil count >400/µL (versus ?400/µL) increased the likelihood of two or more exacerbations >1.4-fold (odds ratio [OR]: 1.48 (95% confidence interval [CI]: 1.39, 1.58); P<0.001). Variables that significantly increased the odds by up to 1.4-fold included increasing age (per year), female gender (versus male), being overweight or obese (versus normal body mass index), being a smoker (versus nonsmoker), having anxiety/depression, diabetes, eczema, gastroesophageal reflux disease, or rhinitis, and prescription for acetaminophen or nonsteroidal anti-inflammatory drugs. Compared with treatment at British Thoracic Society step 2 (daily controller ± reliever), treatment at step 0 (none) or 1 (as-needed reliever) increased the odds by 1.2- and 1.6-fold, respectively, and treatment at step 3, 4, or 5 increased the odds by 1.3-, 1.9-, or 3.1-fold, respectively (all P<0.05). Acute OCS use was the single best predictor of two or more exacerbations. Even one course increased the odds by more than threefold (OR: 3.75 [95% CI: 3.50, 4.01]; P<0.001), and three or more courses increased the odds by >25-fold (OR: 25.7 [95% CI: 23.9, 27.6]; P<0.001).

Conclusion: Blood eosinophil count and several other variables routinely available in patient records may be used to predict frequent asthma exacerbations.
1178-6965
1-12
Price, David
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Wilson, Andrew M.
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Chisholm, Alison
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Rigazio, Anna
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Burden, Anne
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Thomas, Michael
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King, Christine
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Price, David
4dee6753-83c4-4b65-aa9d-f4e915018b57
Wilson, Andrew M.
536dc43f-17cb-4501-8d07-ec938676a0f6
Chisholm, Alison
b9c6e5d9-a4f3-4d05-aaa4-a1435fdc7771
Rigazio, Anna
6c58e9a4-c59d-4993-a86c-05ac99752718
Burden, Anne
8b02859f-a352-4559-b885-ecd6697818aa
Thomas, Michael
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King, Christine
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Price, David, Wilson, Andrew M., Chisholm, Alison, Rigazio, Anna, Burden, Anne, Thomas, Michael and King, Christine (2016) Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice. Journal of Asthma and Allergy, 2016 (9), 1-12. (doi:10.2147/JAA.S97973). (PMID:26793004)

Record type: Article

Abstract

Purpose: Acute, severe asthma exacerbations can be difficult to predict and thus prevent. Patients who have frequent exacerbations are of particular concern. Practical exacerbation predictors are needed for these patients in the primary-care setting.

Patients and methods: Medical records of 130,547 asthma patients aged 12–80 years from the UK Optimum Patient Care Research Database and Clinical Practice Research Datalink, 1990–2013, were examined for 1 year before (baseline) and 1 year after (outcome) their most recent blood eosinophil count. Baseline variables predictive (P<0.05) of exacerbation in the outcome year were compared between patients who had two or more exacerbations and those who had no exacerbation or only one exacerbation, using uni- and multivariable logistic regression models. Exacerbation was defined as asthma-related hospital attendance/admission (emergency or inpatient) or acute oral corticosteroid (OCS) course.

Results: Blood eosinophil count >400/µL (versus ?400/µL) increased the likelihood of two or more exacerbations >1.4-fold (odds ratio [OR]: 1.48 (95% confidence interval [CI]: 1.39, 1.58); P<0.001). Variables that significantly increased the odds by up to 1.4-fold included increasing age (per year), female gender (versus male), being overweight or obese (versus normal body mass index), being a smoker (versus nonsmoker), having anxiety/depression, diabetes, eczema, gastroesophageal reflux disease, or rhinitis, and prescription for acetaminophen or nonsteroidal anti-inflammatory drugs. Compared with treatment at British Thoracic Society step 2 (daily controller ± reliever), treatment at step 0 (none) or 1 (as-needed reliever) increased the odds by 1.2- and 1.6-fold, respectively, and treatment at step 3, 4, or 5 increased the odds by 1.3-, 1.9-, or 3.1-fold, respectively (all P<0.05). Acute OCS use was the single best predictor of two or more exacerbations. Even one course increased the odds by more than threefold (OR: 3.75 [95% CI: 3.50, 4.01]; P<0.001), and three or more courses increased the odds by >25-fold (OR: 25.7 [95% CI: 23.9, 27.6]; P<0.001).

Conclusion: Blood eosinophil count and several other variables routinely available in patient records may be used to predict frequent asthma exacerbations.

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Accepted/In Press date: 12 November 2015
Published date: 7 January 2016
Organisations: Primary Care & Population Sciences

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Local EPrints ID: 391302
URI: http://eprints.soton.ac.uk/id/eprint/391302
ISSN: 1178-6965
PURE UUID: 9c47a124-a18f-48cb-9696-ebc83481e867

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Date deposited: 11 Apr 2016 13:06
Last modified: 14 Mar 2024 23:28

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Contributors

Author: David Price
Author: Andrew M. Wilson
Author: Alison Chisholm
Author: Anna Rigazio
Author: Anne Burden
Author: Michael Thomas
Author: Christine King

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