Development and Validation of the Risk of Exacerbation in Severe Asthma (RESA) Model.

BACKGROUND

Severe asthma (SA) is associated with frequent exacerbations and high treatment costs.

OBJECTIVES

To develop and validate an individualized risk calculator for severe exacerbations in SA, and evaluate its clinical utility for guiding personalized clinical decisions.

METHODS

Patients with SA were identified from combined data from the International Severe Asthma Registry (2015-2022) and NOVEL observational longiTudinal studY (2016-2023) across 30 countries and regions. The prediction end point was the 12-month risk of 1 or more or 2 or more severe exacerbations. Using expert input and Bayesian network analysis, 11 routinely measured predictors were identified, measured within the past 12 months. A mixed-effects, zero-inflated negative binomial model was developed, adjusting for between-country variability and biologic drop-in effects. Internal-external cross-validation was performed using the natural clustering by country settings.

RESULTS

Data from 9911 patients with SA were used. Essential predictors included age, sex, past 12-month severe exacerbations, asthma control, chronic rhinosinusitis, FEV1 to forced vital capacity ratio, percent predicted FEV1, blood eosinophils, fractional exhaled nitric oxide, and long-term oral corticosteroid and macrolide use. The model also adapted setting-specific baseline risks. In the internal-external cross-validation, across broad geographical and health care variability, the model showed excellent calibration and informative, generalizable discrimination (pooled area under the time-dependent receiver-operating characteristics curve of 0.63 [95% CI, 0.60-0.66] for ≥1 and 0.68 [95% CI, 0.64-0.72] for ≥2 exacerbations). Decision curve analysis showed clear net benefit across risk thresholds.

CONCLUSIONS

The Risk of Exacerbation in Severe Asthma model quantifies SA exacerbation risk using routinely available predictors and demonstrates potential clinical utility.