Utilizing CT Based Imaging Parameters of Body Composition to Understand Heterogeneity of Response to Biologic Therapies in Severe Asthma Cohorts

Utilizing CT Based Imaging Parameters of Body Composition to Understand Heterogeneity of Response to Biologic Therapies in Severe Asthma Cohorts

This study will utilize University of Michigan EMR data to form a retrospective cohort of severe asthma patients on biologic therapies for asthma with computed tomography (CT) imaging and known outcomes on therapy. These images will then be analyzed using morphomics, a combination of high-throughput image analysis and deep learning techniques, to derive imaging biomarkers that will be able to predict therapeutic response to biologics. These biomarkers will then be tested in a second cohort from the National Jewish Health to assess for validity.

The two arms for this study represent the two cohorts: the University of Michigan cohort, and the National Jewish Health cohort. The cohorts were split into arms, as the National Jewish Health cohort was intended to act as a validator group for results derived from participants in the University of Michigan cohort.

Inclusion Criteria:

• Asthma diagnosis defined as a positive methacholine test, supportive PFTs, or clinician diagnosis with appropriate supporting clinical context
• Prescribed and taking an FDA-approved biologic medication for severe asthma (mepolizumab, benralizumab, reslizumab, omalizumab, or dupilumab)
• Chest computerized tomography (CT) images taken for any clinical purpose

Exclusion Criteria:

• 10-year history of smoking
• Evidence of emphysema on CT imaging
• Severe bronchiectasis secondary to other causes (subjects with scattered bronchiectasis secondary to severe asthma will not excluded)
• Lack of accessible adequate follow-up information (4 or more months from drug initiation with clear documentation of response) will be excluded from final analysis due to inability to assess response but will be included in the initial cluster identification