International severe asthma registry (ISAR): protocol for a global registry.

BACKGROUND: Severe asthma exerts a disproportionately heavy burden on patients and health care. Due to the heterogeneity of the severe asthma population, many patients need to be evaluated to understand the clinical features and outcomes of severe asthma in order to facilitate personalised and targeted care. The International Severe Asthma Registry (ISAR) is a multi-country registry project initiated to aid in this endeavour. METHODS: ISAR is a multi-disciplinary initiative benefitting from the combined experience of the ISAR Steering Committee (ISC; comprising 47 clinicians and researchers across 29 countries, who have a special interest and/or experience in severe asthma management or establishment and maintenance of severe asthma registries) in collaboration with scientists and experts in database management and communication. Patients (≥18 years old) receiving treatment according to the 2018 definitions of the Global Initiative for Asthma (GINA) Step 5 or uncontrolled on GINA Step 4 treatment will be included. Data will be collected on a core set of 95 variables identified using the Delphi method. Participating registries will agree to provide access to and share standardised anonymous patient-level data with ISAR. ISAR is a registered data source on the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance. ISAR's collaborators include Optimum Patient Care, the Respiratory Effectiveness Group (REG) and AstraZeneca. ISAR is overseen by the ISC, REG, the Anonymised Data Ethics & Protocol Transparency Committee and the ISAR operational committee, ensuring the conduct of ethical, clinically relevant research that brings value to all key stakeholders. CONCLUSIONS: ISAR aims to offer a rich source of real-life data for scientific research to understand and improve disease burden, treatment patterns and patient outcomes in severe asthma. Furthermore, the registry will provide an international platform for research collaboration in respiratory medicine, with the overarching aim of improving primary and secondary care of adults with severe asthma globally.

Real World Biologic Use and Switch Patterns in Severe Asthma: Data from the International Severe Asthma Registry and the US CHRONICLE Study.

INTRODUCTION: International registries provide opportunities to describe use of biologics for treating severe asthma in current clinical practice. Our aims were to describe real-life global patterns of biologic use (continuation, switches, and discontinuations) for severe asthma, elucidate reasons underlying these patterns, and examine associated patient-level factors. METHODS: This was a historical cohort study including adults with severe asthma enrolled into the International Severe Asthma Registry (ISAR; http://isaregistries.org, 2015-2020) or the CHRONICLE Study (2018-2020) and treated with a biologic. Eleven countries were included (Bulgaria, Canada, Denmark, Greece, Italy, Japan, Kuwait, South Korea, Spain, UK, and USA). Biologic utilization patterns were defined: 1) continuing initial biologic; 2) stopping biologic treatment; or 3) switching to another biologic. Reasons for discontinuation/switching were recorded and comparisons drawn between groups. RESULTS: A total of 3531 patients were included. Omalizumab was the most common initial biologic in 2015 (88.2%) and benralizumab in 2019 (29.6%). Most patients (79%; 2791/3531) continued their first biologic; 10.2% (356/3531) stopped; 10.8% (384/3531) switched. The most frequent first switch was from omalizumab to an anti-IL-5/5R (49.6%; 187/377). The most common subsequent switch was from one anti-IL-5/5R to another (44.4%; 20/45). Insufficient efficacy and/or adverse effects were the most frequent reasons for stopping/switching. Patients who stopped/switched were more likely to have a higher baseline blood eosinophil count and exacerbation rate, lower lung function, and greater health care resource utilization. CONCLUSION: The description of real-life patterns of continuing, stopping, or switching biologics enhances our understanding of global biologic use. Prospective studies involving structured switching criteria could ascertain optimal strategies to identify patients who may benefit from switching.

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.

Eosinophilic and Noneosinophilic Asthma: An Expert Consensus Framework to Characterize Phenotypes in a Global Real-Life Severe Asthma Cohort.

BACKGROUND: Phenotypic characteristics of patients with eosinophilic and noneosinophilic asthma are not well characterized in global, real-life severe asthma cohorts. RESEARCH QUESTION: What is the prevalence of eosinophilic and noneosinophilic phenotypes in the population with severe asthma, and can these phenotypes be differentiated by clinical and biomarker variables? STUDY DESIGN AND METHODS: This was an historical registry study. Adult patients with severe asthma and available blood eosinophil count (BEC) from 11 countries enrolled in the International Severe Asthma Registry (January 1, 2015-September 30, 2019) were categorized according to likelihood of eosinophilic phenotype using a predefined gradient eosinophilic algorithm based on highest BEC, long-term oral corticosteroid use, elevated fractional exhaled nitric oxide, nasal polyps, and adult-onset asthma. Demographic and clinical characteristics were defined at baseline (ie, 1 year before or closest to date of BEC). RESULTS: One thousand seven hundred sixteen patients with prospective data were included; 83.8% were identified as most likely (grade 3), 8.3% were identified as likely (grade 2), and 6.3% identified as least likely (grade 1) to have an eosinophilic phenotype, and 1.6% of patients showed a noneosinophilic phenotype (grade 0). Eosinophilic phenotype patients (ie, grades 2 or 3) showed later asthma onset (29.1 years vs 6.7 years; P < .001) and worse lung function (postbronchodilator % predicted FEV1, 76.1% vs 89.3%; P = .027) than those with a noneosinophilic phenotype. Patients with noneosinophilic phenotypes were more likely to be women (81.5% vs 62.9%; P = .047), to have eczema (20.8% vs 8.5%; P = .003), and to use anti-IgE (32.1% vs 13.4%; P = .004) and leukotriene receptor antagonists (50.0% vs 28.0%; P = .011) add-on therapy. INTERPRETATION: According to this multicomponent, consensus-driven, and evidence-based eosinophil gradient algorithm (using variables readily accessible in real life), the severe asthma eosinophilic phenotype was more prevalent than previously identified and was phenotypically distinct. This pragmatic gradient algorithm uses variables readily accessible in primary and specialist care, addressing inherent issues of phenotype heterogeneity and phenotype instability. Identification of treatable traits across phenotypes should improve therapeutic precision.