New tool improves asthma prediction, prevention


Predicting the likelihood that a child will develop asthma has long been a challenge, but a new tool could offer more than previous assessments.

headshot of Gurjit K Khurana Hershey, MD, PhD

Gurjit K Khurana Hershey, MD, PhD

headshot of Jocelyn M Biagini Myers, PhD

Jocelyn M Biagini Myers, PhD

headshot of James E Gern, MD

James E Gern, MD

Researchers have developed a new app that may help clinicians predict which children are at mild to moderate risk of developing asthma, compared with previous assessments that were only able to identify higher-risk patients.

The assessment, called the Pediatric Risk Asthma Score (PARS), was developed by researchers at the University of Cincinnati and Cincinnati Children’s Hospital Medical Center (CCHMC), Cincinnati, Ohio, and published in the Journal of Asthma and Clinical Immunology.1 Coauthor of the report Gurjit K. Khurana Hershey, MD, PHD, Kindervelt Endowed Chair in Asthma Research, professor of Pediatrics, director of the Asthma Research division, co-director of the Office of Pediatric Clinical Fellowship, and attending physician at the CCHMC and director of the medical scientist training program at the University of Cincinnati College of Medicine, says the assessment will be most valuable for use with young children who have experienced wheezing by ages 1 and 2 years.

“Parents often ask, ‘does this mean my child will have asthma?’ or ‘what is my child’s risk of asthma?’” she says. “Now we can answer that more accurately.”

Asthma affects 25.7 million Americans including 7 million children, and costs $5 billion globally each year in drug costs alone, according to the report. Prevention of the disease has long been difficult, partly because clinicians have largely been unable to predict an individual’s risk of developing asthma. The National Institutes of Health has identified zeroing in on better predicting asthma risk as a goal, and several attempts have been made to reach this goal. The Asthma Predictive Index (API), developed in 2004, has been generally accepted as the most valid tool developed so far, according to the report. Although this tool is useful in identifying children who will not have asthma, researchers who developed the PARS tool say the API “leaves much room for improvement in terms of identifying children who will have asthma.”

Assessment beyond the API

The research team that developed the PARS reported working to create a tool that would take into consideration more stringent, personal criteria than the API, including sensitization to allergens and food allergies.

To create the PARS tool, the research team used the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) birth cohort and developed a personalized, predictive algorithm that integrates both clinical and demographic factors. The tool was tested against the API, and findings were replicated using the Isle of Wight birth cohort in addition to the CCAAPS cohort, according to the report.

Of the 762 participants in the CCAAPS cohort, researchers note that 589 were objectively assessed for asthma by age 7 years and that prevalence was 16%. Some of the factors included in the predictive analysis of the tool include incidence of parental asthma, early wheezing by the child, wheezing outside a cold, eczema, age, gender, race, and skin-prick test results. According to the data, the children who had asthma at age 7 years were more likely to have a parent with asthma; eczema before age 3 years; a wheeze apart from the occurrence of a cold; early or frequent generalized wheezing; diagnosis of or probable presence of allergic rhinitis before age 3 years; have 2 or more positive skin-prick test responses to allergens or foods; or be African American.

When the PARS was compared with the API, the research team noted that the PARS tool was more effective at predicting asthma incidence in children with lower risk scores.

A superior predictor for asthma

“The PARS is superior to the API in predicting asthma, especially in children with mild to moderate risk. The API misses 40% of children with mild to moderate risk who go on to develop asthma,” Khurana Hershey says. “This is highly relevant, as these children may be the most amenable to prevention strategies. Future studies may incorporate genetics and other biomarkers into the risk assessment. If we can predict who will develop disease, we might be able to prevent the disease or intervene earlier to help alleviate worsening of the disease or reduce exacerbations.”

The PARS tool offers a continuous risk score with increased sensitivity over previous predictive models, according to the study, with the success of PARS primarily attributed to being able to predict asthma in children with mild to moderate risk-a population the API typically missed.

“The PARS is superior to API with an 11% increase in sensitivity. This increase is due to improved prediction in children with mild to moderate asthma risk. Specifically, the API identifies children at the highest risk for asthma,” the report concludes, with research noting the importance of increased recognition of children in less severe risk categories. “Children with mild to moderate risk have fewer risk factors and might be the most likely to respond favorably to prevention strategies. This is critical because the API and modified API (mAPI) are used to populate asthma prevention trials.”

One of these trials, according to the study, was the Prevention of Early Asthma in Kids (PEAK) trial, which investigated whether asthma prevalence in children aged younger than 3 years could be mitigated with certain therapies. By using a tool like PARS, this study could have included not just children in the high-risk category, but children at mild to moderate risk of developing asthma, the report notes-a population change that could have impacted the results of the study.

“It is critical to correctly identify children across the spectrum of asthma risk because the efficacy of preventions and interventions might be greater in those with mild to moderate risk,” the research team notes.

“Past prevention studies have failed. This may be due in part to the fact that the children that were included in the studies were chosen based on the API. Their risk may have been too high or their disease already too advanced for prevention to be successful,” Khurana Hershey adds. “Future prevention studies using the PARS to select children for prevention interventions will be very useful and have the potential for tremendous impact.”

The PARS tool is already being used by clinicians, says lead author Jocelyn M. Biagini Myers, PhD, associate professor, Department of Pediatrics, Division of Asthma Research, University of Cincinnati and CCHMC, with 3449 users in 75 countries around the world. The tool can be downloaded in the Google Play and Apple App stores, and has been built into the Epic electronic medical record system at CCHMC. She says work will continue to improve the tool, such as performing additional studies to include other racial and ethnic groups in which asthma rates might be higher. She adds that the tool is designed to be used in general practice, not just by specialists or pulmonologists.

Wheezing vs asthma

James E. Gern, MD, a professor of Pediatrics with a focus on asthma at the University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, is one of the clinicians already using the PARS in practice, and says it is a step toward finding better ways to predict which children are at greatest risk of developing asthma.

“It remains difficult to predict which wheezing infants will go on to develop asthma,” Gern says. “Improved prediction would be useful for several reasons. First of all, it would help pediatricians and asthma specialists to provide more accurate information about prognosis to parents of wheezing infants. Second, there are a number of new approaches to asthma prevention that are under development. Clinical trials to test the efficacy of new preventive strategies will depend on being able to gauge the risk for asthma before it has actually developed.”

Gern says both the API and PARS were designed to use easily available information to estimate asthma risk, but whereas the outcomes from API are binary-revealing only high or low risk-the PARS provides a more continuous estimate of risk for children in more moderate categories.

“The PARS can provide improved estimates of asthma risk,” Gern concludes. “This should be of immediate benefit to providing more accurate prognosis to families of wheezing infants and is likely to be quite useful in identifying infants at risk for asthma who could benefit from interventions aimed at prevention.”


1. Biagini Myers JM, Schauberger E, He H, et al. A Pediatric Asthma Risk Score to better predict asthma development in young children. J Allergy Clin Immunol. December 7, 2018. Epub ahead of print. Available at: Accessed January 17, 2019.



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