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External validation of the Predicting Asthma Risk in Children tool in a clinical cohort
Daria O Berger1,2, Eva S L Pedersen1, Maria C Mallet1,2
1Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Insights
The Predicting Asthma Risk in Children (PARC) tool shows potential for ruling out asthma in young children. However, its performance in clinical settings suggests a need for new tools tailored for pediatric pulmonology clinics.
Area of Science:
- Pediatric respiratory health
- Clinical prediction modeling
- Asthma epidemiology
Background:
- The Predicting Asthma Risk in Children (PARC) tool predicts childhood asthma using preschooler symptoms.
- Previous validation was limited to population cohorts, not clinical settings.
Purpose of the Study:
- To externally validate the PARC tool in a pediatric pulmonology clinic.
- To assess the tool's performance in a real-world clinical environment.
Main Methods:
- Utilized the Swiss Paediatric Airway Cohort (SPAC), a prospective cohort of children aged 1-6 years.
- Assessed asthma prediction using sensitivity, specificity, NPV, PPV, AUC, Brier's score, and R².
- Compared SPAC performance to the original Leicester Respiratory Cohort (LRC) validation data.
Main Results:
- In the SPAC cohort (n=346), 36% met the asthma outcome after 2 years.
- At a PARC score of 4, sensitivity was 95% (vs. 79% in LRC), specificity 14% (vs. 57% in LRC).
- AUC (0.71 vs. 0.78) and R² (0.18 vs. 0.28) were lower in SPAC compared to LRC.
Conclusions:
- The PARC tool demonstrates clinical utility for excluding asthma development in young children.
- Performance limitations in the clinical setting indicate a need for novel prediction tools developed specifically for pediatric pulmonology practice.
Introduction:
The Predicting Asthma Risk in Children (PARC) tool uses questionnaire-based respiratory symptoms collected from preschool children to predict asthma risk 5 years later. The tool was developed and validated in population cohorts but not validated using a clinical cohort. We aimed to externally validate the PARC tool in a pediatric pulmonology clinic setting.
Methods:
The Swiss Paediatric Airway Cohort (SPAC) is a prospective cohort of children seen in pediatric pulmonology clinics across Switzerland. We included children aged 1-6 years with cough or wheeze at baseline who completed the 2-year follow-up questionnaire. The outcome was defined as current wheeze plus use of asthma medication. We assessed performance using: sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV), area under the curve (AUC), scaled Brier's score, and Nagelkerke's R2 scores. We compared performance in SPAC to that in the original population, the Leicester Respiratory Cohort (LRC).
Results:
Among 346 children included, 125 (36%) reported the outcome after 2 years. At a PARC score of 4: sensitivity was higher (95% vs. 79%), specificity lower (14% vs. 57%), and NPV and PPV comparable (0.84 vs. 0.87 and 0.37 vs. 0.42) in SPAC versus LRC. AUC (0.71 vs. 0.78), R2 (0.18 vs. 0.28) and Brier's scores (0.13 vs. 0.22) were lower in SPAC.
Conclusions:
The PARC tool shows some clinical utility, particularly for ruling out the development of asthma in young children, but performance limitations highlight the need for new prediction tools to be developed specifically for the clinical setting.
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