Predicting Which Patients Benefit from Biologics in Severe Asthma

Biologic therapies have reshaped the treatment landscape for severe asthma, offering targeted approaches that reduce exacerbations, improve lung function, and decrease reliance on oral corticosteroids. However, treatment response remains variable. Real-world studies suggest that 15% to 17% of patients may not respond to biologics, while partial responses occur in up to 43% to 69%. This highlights a persistent challenge: determining which patients are most likely to benefit from a specific therapy.

A recent systematic review and meta-analysis explored whether a patient’s response to several biologic therapies used in severe asthma could be predicted, including agents targeting IL-5/IL-5R (mepolizumab, benralizumab), IL-4Rα (dupilumab), and thymic stromal lymphopoietin (tezepelumab).

These therapies target pathways involved in type-2 (T2) inflammation, a dominant immunologic driver in many cases of severe asthma characterized by eosinophilic airway inflammation and cytokine signaling through interleukins such as IL-4 and IL-5.

Here’s a brief look at the study and its findings.

Study Design

The investigators conducted a systematic search across four bibliographic databases and two clinical trial registries covering studies published from 1990 to January 2024. The review included clinical trials, observational studies, and real-world cohorts examining predictors of biologic response in patients with severe asthma.

The review identified 21 eligible studies from an initial pool of 5,853 records screened during the literature search. These studies evaluated several biologic therapies used in severe asthma, including mepolizumab (13 studies), benralizumab (6 studies), dupilumab (3 studies), and tezepelumab (1 study). Across the included studies, sample sizes ranged from 20 to 822 participants, with most investigations conducted in real-world clinical settings rather than strictly controlled trial environments. Treatment response was assessed using a range of clinically relevant outcomes, including exacerbation rates, lung function—most commonly measured by forced expiratory volume in one second (FEV₁)—oral corticosteroid (OCS) use, asthma control scores, and patient-reported quality-of-life measures.

Evidence quality was assessed using the CASP risk-of-bias checklist and a modified GRADE framework, allowing the authors to classify predictors according to the strength and certainty of evidence.

Key Predictors of Biologic Response

Several clinical and biomarker-based predictors emerged with moderate-to-high certainty. Elevated markers of T2 inflammation were the most consistent predictors:

• Blood eosinophil counts ≥300 cells/μL were associated with improved responses to mepolizumab, dupilumab, and tezepelumab, including reduced exacerbations and improved lung function.
• Fractional exhaled nitric oxide (FeNO) >40 ppb predicted response to benralizumab, while FeNO levels between 25 and 50 ppb were linked to improved outcomes with dupilumab, including reductions in exacerbation risk and oral corticosteroid use.

FeNO reflects airway inflammation driven by cytokine signaling in the T2 pathway, and its measurement through exhaled breath analysis provides a noninvasive biomarker of airway inflammatory activity.

Clinical Treatment Factors

Baseline corticosteroid exposure also influenced treatment response. Low or absent oral corticosteroid use (<10 mg/day) predicted better outcomes with both mepolizumab and dupilumab, including reduced exacerbations and greater likelihood of achieving steroid-free status.

Asthma control at baseline also appeared informative. Patients with better baseline asthma control scores were more likely to achieve clinical response with mepolizumab and sustained response to benralizumab when assessed after three months of therapy.

Clinical Interpretation

Taken together, these findings reinforce the central role of T2 inflammatory biomarkers, particularly blood eosinophils and FeNO, in guiding biologic therapy selection for severe asthma. At the same time, the review highlights a broader challenge: variability in how studies define treatment response, which complicates cross-study comparisons and meta-analysis. Evidence gaps remain, though. Few studies evaluated pediatric populations, and predictors of response in non-T2 asthma phenotypes were largely absent.

As biologics become increasingly integrated into severe asthma management, refining patient selection remains a priority. Standardized response definitions and large real-world cohorts will be essential to identify reliable predictive markers beyond traditional inflammatory indicators. Ultimately, improving prediction of treatment response could help clinicians move closer to a central goal of modern asthma care: matching the right biologic therapy to the right patient at the right time.

Reference:

Rattu A, Dixey P, Charles D, et al. Predictors of Response to Biologics for Severe Asthma: A Systematic Review and Meta-Analysis. Allergy. 2026;81(1):24-55. doi:10.1111/all.70031