Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice
Authors Price DB, Wilson A, Chisholm A, Rigazio A, Burden A, Thomas M, King C
Received 12 October 2015
Accepted for publication 12 November 2015
Published 7 January 2016 Volume 2016:9 Pages 1—12
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Amrita Dosanjh
David Price,1,2 Andrew M Wilson,3 Alison Chisholm,4 Anna Rigazio,2 Anne Burden,2 Michael Thomas,5 Christine King2
1Centre for Academic Primary Care, The Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, 2Research in Real-Life, Cambridge, 3Norwich Medical School, University of East Anglia, Norwich, 4Respiratory Effectiveness Group, Cambridge, 5Primary Medical Care, University of Southampton, Southampton, UK
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.
Keywords: exacerbator, risk, multiple, hospitalization
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