Abstract
<jats:p>Prediction models for asthma remission in school-age are lacking, limiting clinicians' ability to tailor follow-up. Most prediction tools focus on pre-school diagnosis or require lung function testing. We developed and validated a simple, history-based clinical prediction tool for asthma remission. We analyzed prospective data from the Swiss Paediatric Airway Cohort (SPAC), including 1860 children (aged 5-16 years) with physician-diagnosed asthma. We derived asthma remission predictors from parental questionnaires capturing demographics, symptoms, triggers, and family history. We defined clinical remission at 2-3 years following asthma diagnosis, as absence of wheeze and inhaler use during the past 12 months. We developed the model using LASSO regression with multiple imputations for missing data, and assessed its performance by area under the curve (AUC), Hosmer-Lemeshow (HL) test, and calibration plots. We then derived a simplified score and validated it in the German All-Age Asthma Cohort (ALLIANCE). From 12 candidate variables, the final score retained: sex, wheeze frequency, night-time awakening, exercise-induced wheeze, pollen-triggered wheeze, animal-triggered wheeze, maternal asthma, and paternal asthma. The score demonstrated moderate discrimination in the development cohort (AUC 0.71) and maintained discriminative ability in the external validation (AUC 0.71). This practical, prognostic tool for asthma remission based only on clinical history, allows clinicians to identify children who have lower chances for remission, enabling their closer monitoring.</jats:p>