Disease Burden and Access to Biologic Therapy in Patients with Severe Asthma, 2017-2022: An Analysis of the International Severe Asthma Registry.

Introduction: Patients with severe asthma may be prescribed biologic therapies to improve disease control. The EVEREST study aimed to characterize the global disease burden of patients with severe asthma without access to biologics and those who have access but do not receive biologics, as well as the remaining unmet need despite use of these therapies.

Methods: This was a historical cohort study of patients with severe asthma (aged ≥18 years) in the International Severe Asthma Registry receiving Global Initiative for Asthma (GINA) 2018 step 5 treatment, or with uncontrolled disease at GINA step 4.

Real-world biologics response and super-response in the International Severe Asthma Registry cohort.

Background: Biologic asthma therapies reduce exacerbations and long-term oral corticosteroids (LTOCS) use in randomized controlled trials (RCTs); however, there are limited data on outcomes among patients ineligible for RCTs. Hence, we investigated responsiveness to biologics in a real-world population of adults with severe asthma.

Methods: Adults in the International Severe Asthma Registry (ISAR) with ≥24 weeks of follow-up were grouped into those who did, or did not, initiate biologics (anti-IgE, anti-IL5/IL5R, anti-IL4/13).

Exploring Definitions and Predictors of Response to Biologics for Severe Asthma.

Background: Biologic effectiveness is often assessed as response, a term that eludes consistent definition. Identifying those most likely to respond in real-life has proven challenging.

Objective: To explore definitions of biologic responders in adults with severe asthma and investigate patient characteristics associated with biologic response.

Longitudinal patterns of intermittent oral corticosteroid therapy for asthma in the United Kingdom.

Background: Increasing frequency of intermittent oral corticosteroid (OCS) prescription and cumulative OCS exposure increase the risk of OCS-related adverse outcomes.

Objective: We sought to describe the evolution and trajectory of intermittent OCS prescription patterns in patients with asthma and investigate risk factors independently associated with transitioning to a frequent prescription pattern.

Methods: This historical cohort study included patients with active asthma managed in UK primary care and included in the Optimum Patient Care Research Database (OPCRD; opcrd.

Trends in Systemic Glucocorticoid Utilization in the United Kingdom from 1990 to 2019: A Population-Based, Serial Cross-Sectional Analysis.

Purpose: Associations between systemic glucocorticoid (SGC) exposure and risk for adverse outcomes have spurred a move toward steroid-sparing treatment strategies. Real-world changes in SGC exposure over time, after the introduction of steroid-sparing treatment strategies, reveal areas of successful risk mitigation as well as unmet needs.

Patients And Methods: A population-based ecological study was performed from the Optimum Patient Care Research Database to describe SGC prescribing trends of steroid-sparing treatment strategies in primary care practices before and after licensure of biologics in the United Kingdom from 1990 to 2019.

The future of allergic rhinitis management: A partnership between healthcare professionals and patients.

Allergic rhinitis (AR) is a chronic respiratory condition that internationally continues to be burdensome and impacts quality of life. Despite availability of medicines and guidelines for healthcare providers for the optimal management of AR, optimisation of its management in the community continues to be elusive. The reasons for this are multi-faceted and include both environmental and healthcare related factors.

Predictors of persistent poor control and validation of ASSESS score: Longitudinal 5-year follow-up of severe asthma cohort.

Background: Longitudinal predictors of persistent poor asthma control in severe asthma (SA) cohort remain scarce. The predictive value of the asthma severity scoring system (ASSESS) in the SA cohort outside the original study and in the Asian population is unknown.

Objective: We sought to determine the 5-year longitudinal outcome of patients with SA and validate the use of ASSESS score in predicting future outcomes in SA.

Impact of pre-biologic impairment on meeting domain-specific biologic responder definitions in patients with severe asthma.

Background: There is little agreement on clinically useful criteria for identifying real-world responders to biologic treatments for asthma.

Objective: To investigate the impact of pre-biologic impairment on meeting domain-specific biologic responder definitions in adults with severe asthma.

Methods: This was a longitudinal, cohort study across 22 countries participating in the International Severe Asthma Registry (https://isaregistries.

Does mixing inhaler devices lead to unchecked inhaler technique errors in patients with COPD? Findings from the cross-sectional observational MISMATCH study.

Background: Patients with chronic obstructive pulmonary disease (COPD) may be prescribed multiple inhalers that require different techniques for optimal performance. Mixing devices has been associated with poorer COPD outcomes suggesting that it leads to inappropriate inhaler technique. However, empirical evidence is lacking.

Handling Class Imbalance in Machine Learning-based Prediction Models: A Case Study in Asthma Management.

A data-driven prediction tool has the potential to provide early warning of an asthma attack and improve asthma management and outcomes. Most previous machine learning (ML)-based studies for asthma attack prediction have reported a severe class imbalance, with major implications for model performance. We aimed to undertake a systematic comparison of several class imbalance handling techniques in the context of risk prediction models for asthma prognosis.

Adult Severe Asthma Registries: A Global and Growing Inventory.

Aim: The International Severe Asthma Registry (ISAR; http://isaregistries.org/) uses standardised variables to enable multi-country and adequately powered research in severe asthma. This study aims to look at the data countries within ISAR and non-ISAR countries reported collecting that enable global research that support individual country interests.

Greenhouse Gas Emissions from Respiratory Treatments: Results from the SABA CARBON International Study.

Introduction: Healthcare systems are looking to reduce their carbon impact. Short-acting β-agonist (SABA) overuse (≥ 3 canisters/year) is common in asthma and linked to poor outcomes; however, its environmental impact remains unknown. As part of the CARBON programme, this study retrospectively quantified the carbon footprint of SABA and controller inhalers across all respiratory indications and SABA overuse in asthma in lower-middle-income countries (LMICs), upper-middle-income countries and high-income countries across Africa, Asia Pacific, Latin America and the Middle East.

Impact of Initiating Biologics in Patients With Severe Asthma on Long-Term Oral Corticosteroids or Frequent Rescue Steroids (GLITTER): Data From the International Severe Asthma Registry.

Background: Effectiveness of biologics has neither been established in patients with high oral corticosteroid exposure (HOCS) nor been compared with effectiveness of continuing with HOCS alone.

Objective: To examine the effectiveness of initiating biologics in a large, real-world cohort of adult patients with severe asthma and HOCS.

Methods: This was a propensity score-matched, prospective cohort study using data from the International Severe Asthma Registry.

Comparative effectiveness of anti-IL5 and anti-IgE biologic classes in patients with severe asthma eligible for both.

Background: Patients with severe asthma may present with characteristics representing overlapping phenotypes, making them eligible for more than one class of biologic. Our aim was to describe the profile of adult patients with severe asthma eligible for both anti-IgE and anti-IL5/5R and to compare the effectiveness of both classes of treatment in real life.

Methods: This was a prospective cohort study that included adult patients with severe asthma from 22 countries enrolled into the International Severe Asthma registry (ISAR) who were eligible for both anti-IgE and anti-IL5/5R.

Individualised risk prediction model for exacerbations in patients with severe asthma: protocol for a multicentre real-world risk modelling study.

Introduction: Severe asthma is associated with a disproportionally high disease burden, including the risk of severe exacerbations. Accurate prediction of the risk of severe exacerbations may enable clinicians to tailor treatment plans to an individual patient. This study aims to develop and validate a novel risk prediction model for severe exacerbations in patients with severe asthma, and to examine the potential clinical utility of this tool.

Observational UK cohort study to describe intermittent oral corticosteroid prescribing patterns and their association with adverse outcomes in asthma.

Introduction: Oral corticosteroids (OCS) for asthma are associated with increased risks of developing adverse outcomes (adverse outcomes); no previous study has focused exclusively on intermittent OCS use.

Methods: This historical (2008-2019) UK cohort study using primary care medical records from two anonymised, real-life databases (OPCRD and CPRD) included patients aged≥4 years with asthma receiving only intermittent OCS. Patients were indexed on their first recorded intermittent OCS prescription for asthma and categorised by OCS prescribing patterns: one-off (single), less frequent (≥90 day gap) and frequent (<90 day gap).

Defining clinical subtypes of adult asthma using electronic health records: Analysis of a large UK primary care database with external validation.

Introduction: Asthma is one of the commonest chronic conditions in the world. Subtypes of asthma have been defined, typically from clinical datasets on small, well-characterised subpopulations of asthma patients. We sought to define asthma subtypes from large longitudinal primary care electronic health records (EHRs) using cluster analysis.