Individual Risk Assessment Tool for School Age Asthma Prediction in UK Birth Cohort

Abstract

Background

Current published asthma predictive tools have moderate positive likelihood ratios (LR+) but high negative likelihood ratios (‐LR) based on their recommended cut‐offs, which limit their clinical usefulness.

Objective

To develop a simple clinically applicable asthma prediction tool within a population‐based birth cohort.

Method

Children from the Manchester Asthma and Allergy Study (MAAS) attended follow‐up at ages 3, 8 and 11 years. Data on pre‐school wheeze was extracted from primary‐care records. Parents completed validated respiratory questionnaires. Children were skin prick tested (SPT). Asthma at 8/11 years (school ‐age) was defined as parentally‐reported (1) physician‐diagnosed asthma and wheeze in the previous 12 months or (2) ≥3 wheeze attacks in the previous 12 months. An asthma prediction tool (MAAS APT) was developed using logistic regression of characteristics at age 3 years to predict school‐age asthma.

Results

Of 336 children with physician‐confirmed wheeze by age 3 years, 117(35%) had school‐age asthma. Logistic regression selected 5 significant risk factors which formed the basis of the MAAS APT: wheeze after exercise; wheeze causing breathlessness; cough on exertion; current eczema and SPT sensitisation(maximum score 5). A total of 281(84%) children had complete data at age 3 years and were used to test the MAAS APT. Children scoring ≥3 were at high risk of having asthma at school‐age(PPV>75%; +LR 6.3,‐LR 0.6), whereas children who had a score of 0 had very low risk(PPV 9.3%; LR 0.2).

Conclusion

MAAS APT is a simple asthma prediction tool which could easily be applied in clinical and research settings.

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