Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials

Abstract

Background Individualized prediction of treatment response may improve the value proposition of advanced treatment options in severe asthma. This study aimed to investigate the combined capacity of patient characteristics in predicting treatment response to mepolizumab in patients with severe asthma. Methods Patient-level data were pooled from two multinational phase 3 trials of mepolizumab in severe eosinophilic asthma. We fitted penalized regression models to quantify reductions in the rate of severe exacerbations and the 5-item Asthma Control Questionnaire (ACQ5) score. The capacity of 15 covariates towards predicting treatment response was quantified by the Gini index (measuring disparities in treatment benefit) as well as observed treatment benefit within the quintiles of predicted treatment benefit. Results There was marked variability in the ability of patient characteristics to predict treatment response; covariates explained greater heterogeneity in predicting treatment response to asthma control than to exacerbation frequency (Gini index 0.35 v. 0.24). Key predictors for treatment benefit for severe exacerbations included exacerbation history, blood eosinophil count, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of nasal polyps. Overall, the average reduction in exacerbations was 0.90/year (95%CI, 0.87‒0.92) and average reduction in ACQ5 score was 0.18 (95% CI, 0.02‒0.35). Among the top 20% of patients for predicted treatment benefit, exacerbations were reduced by 2.23/year (95% CI, 2.03‒2.43) and ACQ5 score were reduced by 0.59 (95% CI, 0.19‒0.98). Among the bottom 20% of patients for predicted treatment benefit, exacerbations were reduced by 0.25/year (95% CI, 0.16‒0.34) and ACQ5 by -0.20 (95% CI, -0.51 to 0.11). Conclusion A precision medicine approach based on multiple patient characteristics can guide biologic therapy in severe asthma, especially in identifying patients who will not benefit as much from therapy. Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation. Trial registration ClinicalTrials.gov number, NCT01691521 (registered September 24, 2012) and NCT01000506 (registered October 23, 2009).

Promising treatment biomarkers in asthma

“…The DREAM RCT showed that the effects of mepolizumab were enhanced in patients with elevated blood eosinophils, and in those with higher airway reversibility (Ortega H. et al, 2014), and post hoc analyses of data from the DREAM and MENSA RCTs showed that the exacerbation rate reduction with mepolizumab increased progressively from 52% in patients with blood eosinophil count ≥150 cells/µL to 70% in patients with blood eosinophil count ≥500 cells/µL (Ortega et al, 2016). Other key predictors for treatment benefit for severe exacerbations included exacerbation history, baseline ACQ5 score and age, and those for symptom control included blood eosinophil count and presence of chronic rhinosinusitis with nasal polyps, which also benefitted from the treatment (Chen et al, 2023;Chupp et al, 2023;Liu et al, 2023). In the MAPLE trial on 27 patients treated with mepolizumab, addition of oral corticosteroids had no significant effect on symptoms or quality of life, but they did still improve smallairway obstruction and reduce T2 biomarkers (Yang et al, 2022).…”

The treatable traits approach to adults with obstructive airways disease in primary and secondary care

“…92 More broadly, multiple patient characteristics can be used to not only identify patients likely to have an enhanced response, but also those who likely to obtain minimal benefit from biologic treatments. 93 Such characterization is important, to improve the cost-effectiveness of these expensive therapies, and address the current practice of use beyond their evidence base for efficacy and safety. 94 An important example relevant to COPD is the utility of measurement of the blood eosinophil count to help identify in the clinic those patients with COPD who are likely to benefit most from ICS use at the lowest risk of undesired side effects.…”