A Pediatric Asthma Risk Score to better predict asthma development in young children

Abstract

Background: Asthma phenotypes are currently not amenable to primary prevention or early intervention because their natural history cannot be reliably predicted. Clinicians remain reliant on poorly predictive asthma outcome tools because of a lack of better alternatives.

Objective: We sought to develop a quantitative personalized tool to predict asthma development in young children.

Methods: Data from the Cincinnati Childhood Allergy and Air Pollution Study (n = 762) birth cohort were used to identify factors that predicted asthma development. The Pediatric Asthma Risk Score (PARS) was constructed by integrating demographic and clinical data. The sensitivity and specificity of PARS were compared with those of the Asthma Predictive Index (API) and replicated in the Isle of Wight birth cohort.

Results: PARS reliably predicted asthma development in the Cincinnati Childhood Allergy and Air Pollution Study (sensitivity = 0.68, specificity = 0.77). Although both the PARS and API predicted asthma in high-risk children, the PARS had improved ability to predict asthma in children with mild-to-moderate asthma risk. In addition to parental asthma, eczema, and wheezing apart from colds, variables that predicted asthma in the PARS included early wheezing (odds ratio [OR], 2.88; 95% CI, 1.52-5.37), sensitization to 2 or more food allergens and/or aeroallergens (OR, 2.44; 95% CI, 1.49-4.05), and African American race (OR, 2.04; 95% CI, 1.19-3.47). The PARS was replicated in the Isle of Wight birth cohort (sensitivity = 0.67, specificity = 0.79), demonstrating that it is a robust, valid, and generalizable asthma predictive tool.

Conclusions: The PARS performed better than the API in children with mild-to-moderate asthma. This is significant because these children are the most common and most difficult to predict and might be the most amenable to prevention strategies.

Keywords: Asthma prediction score; childhood asthma; persistent wheezing; sensitization.

Figure 1:

Predicted (closed circle) versus observed (gray bars) asthma prevalence by asthma prediction score in CCAAPS (A) and IOW (B). The green shading depicts the proportion of children that were predicted to have asthma according to the original loose definition of the API of those that were observed to have asthma.

Figure 2:

Comparison of ROC curves between API and PARS. The dotted lines indicate API applied to the two cohorts; solid lines indicate PARS applied to the two cohorts. Blue lines indicate CCAAPS and red lines indicate IOW. Model discrimination was evaluated by the area under ROC curve. Model discrimination for the CCAAPS PARS model was excellent (AUC=0.80; p<0.001) and was significantly higher than the API loose index (p=0.002), and also was higher than the model applying the loose API to CCAAPS (p=0.003). Model discrimination for the IOW PARS model was excellent (AUC=0.80; p<0.001) and was significantly higher than the API loose index (p=0.0004), and also was higher than the model applying the loose API to IOW (p<0.0001). Blue and red triangles are the points at which sensitivity and specificity were assessed for PARS in CCAAPS (≥7) and IOW (≥6), respectively. The shaded gray area between the green and blue lines shows the proportion of children that were missed by the API but detected by PARS.