Background: Asthma attacks are common, serious, and costly. Individual factors associated with attacks, such as poor symptom control, are not robust predictors. Objective: We investigated whether the rich data available in UK electronic medical records could identify patients at risk of recurrent attacks. Methods: We analyzed anonymized, longitudinal medical records of 118,981 patients with actively treated asthma (ages 12-80 years) and ≥3 years of data. Potential risk factors during 1 baseline year were evaluated using univariable (simple) logistic regression for outcomes of ≥2 and ≥4 attacks during the following 2-year period. Predictors with significant univariable association (P<.05) were entered into multiple logistic regression analysis with backwards stepwise selection of the model including all significant independent predictors. The predictive accuracy of the multivariable models was assessed. Results: Independent predictors associated with future attacks included baseline-year markers of attacks (acute oral corticosteroid [OCS] courses, emergency visits), more frequent reliever use and healthcare utilization, worse lung function, current smoking, blood eosinophilia, rhinitis, nasal polyps, eczema, gastroesophageal reflux disease, obesity, older age, and being female. The number of OCS courses had the strongest association. The final cross-validated models incorporated 19 and 16 risk factors for ≥2 and ≥4 attacks over 2 years, respectively, with areas under the curve of 0.785 (95% CI 0.780-0.789) and 0.867 (0.860-0.873
EDITOR'S SPECIFIC COMMENTS:Thank you for submitting your revised manuscript to JACI: In Practice. As you know, we want to publish your work. However, your responses have not satisfied our biostatistical (Reviewer #3). We will accept your paper for publication after the biostatistical reviewer comments have been adequately addressed in a further revision.
RESPONSE:We thank the Editor for the opportunity to address the additional comments from Reviewer 3 regarding our manuscript. Our point-by-point response to the comments is provided below. We hope that you will now find this second revised version of our manuscript suitable for publication in JACI: In Practice. Many thanks for your reconsideration. Best wishes, John Blakey, for the authors Reviewer #1: The authors have responded very well to reviewer input in their revised manuscript.
RESPONSE: Thank you.Reviewer #3 (Biostatistical Reviewer) 3.1. COMMENT: The authors have presented some strong analyses due to sample sizes. There are still a few important points to address and revisions needed to the presentation and discussion of analyses to improve this submission. Many of these issues were identified on the first review but not addressed.
RESPONSE:We thank the Reviewer for these additional comments and suggestions. We hope the following responses address these concerns to the satisfaction of the editorial team.
COMMENT-Methods section:-I do not really understand the study design regarding how the years were selected and why...