Evaluating early-life asthma definitions as a marker for subsequent asthma in an electronic medical record setting

• Type of Material: Article
• Authors: Audrey Flak Pennington, Emory University; Matthew Strickland, Emory University; Karen A. Freedle, Emory University; Mitchel Klein, Emory University; Carolyn Drews-Botsch, Emory University; Craig Hansen, Kaiser Permanente; Lyndsey Darrow, Emory University
• Language: English
• Date: 2016-09-01
• Publisher: Wiley: 12 months
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016 John Wiley & Sons A/S.
• Final Published Version (URL): http://dx.doi.org/10.1111/pai.12586
• Title of Journal or Parent Work: Pediatric Allergy and Immunology
• ISSN: 0905-6157
• Volume: 27
• Issue: 6
• Start Page: 591
• End Page: 596
• Grant/Funding Information: US EPA grant R834799, NIH/NICHD Grant R03HD084884-01, NIH Reproductive, Perinatal, & Pediatric Training Grant T32HD052460.
• Keywords: birth cohort; Life Sciences & Biomedicine; Science & Technology; ASSOCIATION; epidemiology; children; RISK; electronic medical records; DISEASE; Allergy; prediction; Pediatrics; OBESITY; asthma; Immunology; INDEX; YOUNG-CHILDREN; SEVERITY; CARE
• Research Categories: Health Sciences, General; Health Sciences, Public Health

Abstract

Background: Case definitions for asthma incidence in early life vary between studies using medical records to define disease. This study assessed the impact of different approaches to using medical records on estimates of asthma incidence by age 3 and determined the validity of early-life asthma case definitions in predicting school-age asthma. Methods: Asthma diagnoses and medications by age 3 were used to classify 7103 children enrolled in Kaiser Permanente Georgia according to 14 definitions of asthma. School-age asthma was defined as an asthma diagnosis between ages 5 and 8. Sensitivity (probability of asthma by age 3 given school-age asthma), specificity (probability of no asthma by age 3 given no school-age asthma), positive and negative predictive values (probability of (no) school-age asthma given (no) asthma by age 3), and likelihood ratios (combining sensitivity and specificity) were used to determine predictive ability. Results: 9.0–35.2% of children were classified as asthmatic by age 3 depending on asthma case definition. Early-life asthma classifications were more specific than sensitive and were better at identifying children who would not have school-age asthma (negative predictive values: 80.7–86.6%) than at predicting children who would have school-age asthma (positive predictive values: 43.5–71.5%). Conclusions: Choice of case definition had a large impact on the estimate of asthma incidence. While ability to predict school-age asthma was limited, several case definitions performed similarly to clinical asthma prediction tools used in previous asthma research (e.g., the Asthma Predictive Index).