The International Severe Asthma Registry (ISAR)’s new study, “Exploring definitions and predictors of response to biologics for severe asthma”, published in The Journal of Allergy and Clinical Immunology: In Practice (JACI: In Practice), explores the effectiveness of biologic treatments in adults with severe asthma. Given the variability in asthma response based on differing definitions, this study focuses on identifying predictors of response and examining residual symptoms post-treatment.
Including data from 21 countries and 2,210 patients, this study evaluates what response to biologic therapy means in real-life, explores different definitions of response, and identifies patients most likely to achieve it. Response is defined based on changes in four asthma outcome domains over a one-year period before and after initiating biologic treatment. These domains included asthma attacks (exacerbation rate), long-term oral corticosteroid dose, asthma symptoms (control), and lung function, measured by Forced Expiratory Volume in the first second (FEV1).
The study brings to light that the concept of treatment response is intricately tied to baseline severity, affecting clinical outcomes. For instance, a patient experiencing a 50% reduction in exacerbation rate following biologic therapy might still have a high rate of exacerbations post-treatment, indicating significant residual symptoms. This raises important questions about defining treatment success and determining appropriate therapeutic targets, and it suggests that a nuanced approach is needed to set goals that account not only for relative improvements but also for achieving clinically meaningful reductions in symptom burden.
Characteristics that predicted response to biologic treatment depended upon asthma outcome included in the response definition. For example, lung function responders were more likely to have higher pre-biologic FeNO and BEC (inflammatory biomarkers), were older at asthma onset, and had a shorter duration of asthma. Long-term oral corticosteroid use (LTOCS), asthma control and lung function responders were more likely to have higher pre-biologic BEC and presence of Type 2 (inflammatory) diseases, like chronic rhinosinusitis, allergic rhinitis and nasal polyposis. Interestingly, some characteristics increased the odds for response in one area but were reduced in another (see figure 1), giving us new insight into the idea of ‘response’, its complexity, and how it may be influenced by numerous factors
Figure 1. Summary of associations between selected pre-biologic characteristics and response to biologic for each single-domain responder definition
Abbreviations: AD: atopic dermatitis; AR: allergic rhinitis; BEC: blood eosinophil count; BMI: body mass index; CRS: chronic rhinosinusitis; FeNO: fractional exhaled nitric oxide; LTOCS: long-term oral corticosteroid; NP: nasal polyps.
* Statistically significant (p<0.05) association
The study found that response rates varied widely depending on the outcome measured. For example, 80% of patients showed a reduction in asthma exacerbations, while only 10% met the criteria for improvement across all four improvement criteria, suggesting that biologic response should be assessed across multiple domains to capture the full impact on patient health. Additionally, although many patients responded to biologic treatments, they still experienced significant symptoms. For instance, nearly half of the patients who initially had uncontrolled asthma continued to struggle with asthma control even after biologic therapy. Long-term non-reversible lung damage might also limit response in some patients, highlighting the importance of early intervention for optimum outcomes in asthma management. These findings emphasize that assessing and predicting response in real life is complex and variable, much like asthma itself, and that response can be seen as a journey, particularly underlining the importance of lung function in assessment of outcomes.
The key takeaway? The importance of having a patient-centred approach to biologic response interpretation, and the potential benefits of using predictors of response, such as baseline severity and lung function evaluation, to estimate how likely each patient is to respond.
To learn more about the study, please read the full publication in The Journal of Allergy and Clinical Immunology: In Practice (JACI: In Practice), as well as the accompanying slide deck.