Recommended Citation
Biagini J, Martin L, He H, Bacharier L, Gebretsadik T, Hartert T, Jackson D, Kim H, Miller R, Rivera-Spoljaric K, Schauberger E, Singh AM, Visness C, Wegienka G, Ownby D, Gold D, Martinez F, Johnson CC, Wright A, Gern J, and Hershey GK. The Pediatric Asthma Risk Score: A New Gold Standard for Asthma Prediction. J Allergy Clin Immunol 2023; 151(2):AB320.
Document Type
Conference Proceeding
Publication Date
2-1-2023
Publication Title
J Allergy Clin Immunol
Abstract
Rationale: Early prediction of asthma is critical to identify potential primary prevention strategies. The Pediatric Asthma Risk Score (PARS) is a continuous score to predict early-life asthma but was developed and validated in relatively homogenous populations. We compared PARS directly to the Asthma Predictive Index (API) and validated in 10 cohorts with varying race, ethnicity, sex, cohort type, missing data and birth decades, and perform a meta-analysis across all 10 cohorts.
Methods: We utilized data from 5674 children participating in the Children’s Respiratory and Environmental Workgroup. We applied both PARS and the API in each cohort, as well as harmonized across all cohorts, and directly compared the ability of each tool to predict asthma development at ages 5-10.
Results: The PARS area under the curve (AUC) was significantly higher than the AUC of the API in 9 cohorts (p-value range 0.01 - <0.001). The PARS AUC did not differ by cohort type (high risk or general population), decade of enrollment, race, sex, ethnicity, missing PARS factors or polysensitization definition (skin prick test vs. specific IgE). The weights of the 6 PARS factors in the meta-analysis were very similar to the original weights, validating the original PARS scoring.
Conclusions: This multi-cohort study makes the PARS the most validated model of asthma prediction in children to date, not only with respect to the number of cohorts used but also with regards to capturing the diversity of asthma in the United States. Future studies may consider PARS the new gold standard in pediatric asthma risk prediction.
Volume
151
Issue
2
First Page
AB320
