Asthma Phenotyping in Primary Care: Applying the International Severe Asthma Registry Eosinophil Phenotype Algorithm Across All Asthma Severities

Background
We developed an eosinophil phenotype gradient algorithm and applied it to a large severe asthma cohort (International Severe Asthma Registry).
Objective
We sought to reapply this algorithm in a UK primary care asthma cohort, quantify the eosinophilic phenotype, and assess the relationship between the likelihood of an eosinophilic phenotype and asthma severity/health care resource use (HCRU).
Methods
Patients age 13 years and older with active asthma and blood eosinophil count or 1 or greater, who were included from the Optimum Patient Care Research Database and the Clinical Practice Research Datalink, were categorized according to the likelihood of eosinophilic phenotype using the International Severe Asthma Registry gradient eosinophilic algorithm. Patient demographic, clinical and HCRU characteristics were described for each phenotype.
Results
Of 241,006 patients, 50.3%, 22.2%, and 21.9% most likely (grade 3), likely (grade 2), and least likely (grade 1), respectively, had an eosinophilic phenotype, and 5.6% had a noneosinophilic phenotype (grade 0). Compared with patients with noneosinophilic asthma, those most likely to have an eosinophilic phenotype tended to have more comorbidities (percentage with Charlson comorbidity index of ≥2: 28.2% vs 6.9%) and experienced more asthma attacks (percentage with one or more attack: 24.8% vs 15.3%). These patients were also more likely to have asthma that was difficult to treat (31.1% vs 18.3%), to receive more intensive treatment (percentage on Global Initiative for Asthma 2020 step 4 or 5: 44.2% vs 27.5%), and greater HCRU (eg, 10.8 vs 7.9 general practitioner all-cause consultations per year).
Conclusions
The eosinophilic asthma phenotype predominates in primary care and is associated with greater asthma severity and HCRU. These patients may benefit from earlier and targeted asthma therapy.