A precision medicine approach to severe asthma treatment can identify patients who will have minimal benefit from biologic therapy with mepolizumab, based on numerous patient characteristics, according to post-hoc analysis published in Respiratory Research.
Due to the high cost of biologic treatment for asthma, there is value to being able to predict whether a particular patient will achieve benefit from biologic treatment.
Investigators therefore sought to assess whether a combination of patient characteristics in those with severe asthma could predict treatment response to mepolizumab.
Investigators conducted a post-hoc analysis using patient-level data pooled from 2 phase 3 double-blind, placebo-controlled, multinational trials (MENSA and DREAM) of mepolizumab in severe eosinophilic asthma (ClinicalTrials.gov Identifiers: NCT01691521 and NCT01000506). The primary outcome for this analysis was absolute reduction in the rate of severe exacerbations with mepolizumab 75 mg vs placebo in the first year of follow-up; the secondary outcome was reduction in the 5-item Asthma Control Questionnaire (ACQ5) score with mepolizumab 75 mg vs placebo in the first year of follow-up.
Reductions in the ACQ5 score and rate of severe exacerbations were quantified by fitted penalized regression models. The Gini index measured observed treatment benefit and disparities in treatment benefit within the quintiles of predicted treatment benefit of 15 covariates aimed at predicting treatment response.
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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.
In the MENSA trial (38 weeks; N=576), patients were randomly assigned 1:1:1 to receive 75 mg intravenous mepolizumab, 100 mg subcutaneous mepolizumab, or placebo every 4 weeks; in the DREAM trial (52 weeks; N=621) patients were randomly assigned 1:1:1:1 to receive either 75 mg, 250 mg, 750 mg of intravenous mepolizumab or matched placebo every 4 weeks.
For the post hoc analysis, the pooled treatment group consisted of 314 patients (mean age, 49.8 years; 60% women; median follow-up, 235 days) and the related pooled placebo group consisted of 320 patients (mean age, 47.6 years; 60% women; median follow-up, 237 days).
Investigators found that the greater heterogeneity in predicting treatment response to asthma control (Gini index 0.35) than to exacerbation frequency (Gini index 0.24) was explained with the covariates. Major predictors of the benefit of mepolizumab in treating severe asthma exacerbations were baseline ACQ5 score, age, blood eosinophil count, and exacerbation history. Additional predictors included age, long-term oral corticosteroids, and Hispanic ethnicity. Key symptom control predictors were presence of nasal polyps and blood eosinophil count. Additional predictors included Hispanic ethnicity, long-term oral corticosteroids, and asthma duration.
For the entire cohort studied, treatment mepolizumab was associated with an average exacerbation reduction of 0.90/year overall (95% CI, 0.87-0.92) and an average ACQ5 score reduction of 0.18 overall (95% CI, 0.02-0.35). Among the top 20% of patients predicted to benefit from treatment, exacerbations decreased by 2.23/year (95% CI, 2.03-2.43; with a corresponding treatment efficiency increase of 248%) and average ACQ5 scores decreased by 0.59 (95% CI, 0.19-0.98), with a corresponding treatment efficiency improvement of 328%). Among the 20% of patients who were predicted to benefit least from treatment, exacerbations were reduced by 0.25/year (95% CI, 0.16-0.34) and average ACQ5 scores did not decrease (average score reduction, -0.20; 95% CI, -0.51 to 0.11).
Post-hoc analysis limitations include the inclusion of only mepolizumab 75 mg in this analysis (in clinical practice, 100 mg subcutaneous is more widely used) and the unaccounted-for predictive capacity of additional important risk factors.
“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,” investigators concluded. They added “Patient characteristics had a greater capacity to predict treatment response to asthma control than to exacerbation.”
