Three-step algorithm for biological therapy targeted IgE and IL-5 in severe asthma

针对重度哮喘的IgE和IL-5生物疗法的三步算法

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Abstract

INTRODUCTION: Recently, several new biological therapies targeted IgE and IL-5 in severe asthma have been developed and approved. In the last few years, there have been some reports on the therapeutic algorithms for severe asthmatic subjects screened by biomarkers. However, these algorithms have one problem. In atopic/eosinophilic overlapping asthmatic subjects, there is no effective answer to the question: "which is the optimal choice between Anti-IgE and anti-IL-5?" METHODS: We propose a new three-step algorithm for biological therapy in severe asthma. RESULTS: Step 1 is to divide subjects into four groups by measuring blood eosinophils and FeNO. Step 2 is to divide the subjects further into six groups by atopy test. In the case of elevated blood eosinophils, normal/elevated FeNO, and atopy, we perform a steroid trial in step 3 in order to decide whether to select anti-IgE or anti-IL-5. The steroid trial is to assess the symptoms of asthma, lung function, blood eosinophils, and FeNO before and after 14 days treatment with 0.5 mg/kg oral prednisolone/day. We judge that cases in which blood eosinophils and FeNO decrease together are not "truely steroid resistance." In such cases, considering the possibility that allergic type inflammation through adaptive immunity is dominant, anti-IgE is selected when it is difficult to prevent exacerbations by improving environmental factors. Conversely, we consider that cases in which blood eosinophils and/or FeNO do not decrease, are "truely steroid resistance." In this case, since there is a possibility that non-allergic type inflammation due to innate immunity, etc. may remain, anti-IL-5, which is expected to be effective for steroid-resistant eosinophilic inflammation, is selected. CONCLUSIONS: Our three-step algorithm including the steroid trial may be applicable to companion diagnostics testing for molecularly targeted therapies in severe asthma. Further validation is required to examine the effectiveness of this algorithm.

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