Impact of Clinical Characteristics and Biomarkers on AIRQ Exacerbation Prediction Ability

Kevin R Murphy; David A Beuther; Bradley Chipps; Robert A Wise; William McCann; Joan Reibman; Maureen George; Ileen Gilbert; James M Eudicone; Hitesh N Gandhi; Melissa Ross; Karin S Coyne; Robert S Zeiger

doi:10.1016/j.jaip.2024.04.050

Impact of Clinical Characteristics and Biomarkers on AIRQ Exacerbation Prediction Ability

J Allergy Clin Immunol Pract. 2024 May 3:S2213-2198(24)00436-7. doi: 10.1016/j.jaip.2024.04.050. Online ahead of print.

Authors

Affiliations

¹ Boys Town National Research Hospital, Boys Town, NE, United States. Electronic address: kevin.murphy@boystown.org.
² National Jewish Health, Denver, CO, United States. Electronic address: DavidBeuther@NJHealth.org.
³ Capital Allergy & Respiratory Disease Center, Sacramento, CA, United States. Electronic address: bchipps@capitalallergy.com.
⁴ Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States. Electronic address: rwise@jhmi.edu.
⁵ Allergy Partners, Asheville, NC, United States. Electronic address: bmccann@allergypartners.com.
⁶ New York University School of Medicine, New York, NY, United States. Electronic address: Joan.Reibman@nyulangone.org.
⁷ Columbia University School of Nursing, New York, NY, United States. Electronic address: mg3656@cumc.columbia.edu.
⁸ AstraZeneca, Wilmington, DE, United States. Electronic address: ileen.gilbert@astrazeneca.com.
⁹ AstraZeneca, Wilmington, DE, United States. Electronic address: James.Eudicone@astrazeneca.com.
¹⁰ AstraZeneca, Wilmington, DE, United States. Electronic address: hitesh.gandhi@alexion.com.
¹¹ Evidera, Bethesda, MD, United States. Electronic address: melissa.ross@evidera.com.
¹² Evidera, Bethesda, MD, United States. Electronic address: Karin.Coyne@evidera.com.
¹³ Department of Clinical Science, Kaiser Permanente Bernard J. Tyson School of Medicine Pasadena, CA, United States. Electronic address: robert.s.zeiger@kp.org.

PMID: 38705273
DOI: 10.1016/j.jaip.2024.04.050

Abstract

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.

Keywords: asthma; control; exacerbation; impairment; patient-reported outcome; questionnaire; risk; uncontrolled.