Impact of Clinical Characteristics and Biomarkers on AIRQ Exacerbation Prediction Ability

Background Complex models combining impairment-based control assessments with clinical characteristics and biomarkers have been developed to predict asthma exacerbations. The composite Asthma Impairment and Risk Questionnaire (AIRQ) with adjustments for demographics (age, sex, race, body mass index [BMI]) predicts 12-month exacerbation occurrence similarly to these more complex models. Objective To examine whether AIRQ exacerbation prediction is enhanced when models are adjusted for a wider range of clinical characteristics and biomarkers. Methods Patients aged ≥12 years completed monthly online surveys regarding exacerbation-related oral corticosteroid use, emergency-department/urgent-care visits, and hospitalizations. Univariate logistic regressions to predict exacerbations were performed with sociodemographics, comorbidities, exacerbation history, lung function, blood eosinophils, immunoglobulin E, and fractional exhaled nitric oxide. Significant (P≤0.05) variables were included in multivariable logistic regressions with and without AIRQ control categories to predict 12-month exacerbations (log odds ratio [OR], 95% Wald confidence interval [CI]). Model performances were compared. Results Over 12 months, 1070 patients (70% female; mean[SD] age 43.9[19.4] years; 22% non-White; BMI[SD] 30.6[8.7]) completed ≥1 survey (mean[SD] 10.5[2.8]). In the multivariable analysis, AIRQ control category adjusted for significant clinical characteristics and biomarkers was predictive of ≥1 exacerbation: OR(95%CI) not well-controlled vs well-controlled: 1.93(1.41-2.62), very poorly controlled vs well-controlled: 3.81(2.65-5.47). Receiver operating characteristic area under the curve for this more complex model of exacerbation prediction (AUC=0.72) did not differ from AIRQ (AUC=0.70). Models with AIRQ performed better than those without AIRQ (AUC=0.67, P<0.05). Conclusion Costly and time-consuming complex modeling with clinical characteristics and biomarkers does not enhance the strong exacerbation prediction ability of AIRQ.