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IgE, blood eosinophils and FeNO are not enough for choosing a monoclonal therapy among the approved options in patients with type 2 severe asthma

Type-2 inflammation is the most frequent endophenotype of asthma. Different biomarkers have been proposed to identify this inflammation because highly effective therapies have improved type-2 severe asthma control. We investigated the frequency of some biomarkers of type-2 inflammation (total IgE, s...

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Detalles Bibliográficos
Autores principales: Sánchez, Jorge, Morales, Edison, Santamaria, Luis-Carlos, Acevedo, Ana-Milena, Calle, Ana, Olivares, Margarita, Gomez, Carolina, Amaya, Daniel, Cardona, Ricardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: World Allergy Organization 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7941083/
https://www.ncbi.nlm.nih.gov/pubmed/33747341
http://dx.doi.org/10.1016/j.waojou.2021.100520
Descripción
Sumario:Type-2 inflammation is the most frequent endophenotype of asthma. Different biomarkers have been proposed to identify this inflammation because highly effective therapies have improved type-2 severe asthma control. We investigated the frequency of some biomarkers of type-2 inflammation (total IgE, sIgE, blood eosinophil, and FeNO) in the framework of severe asthma and assessed its ability to help us to choose the best biological therapy for each patient. Different scenarios (sensitivity analysis) were evaluated according to the biomarkers proposed for each biological therapy in 72 patients with type-2 severe asthma. Between 54.1% and 68% of patients could receive at least 2 different biological therapies and 34.7%–40.2% could receive any of the 3 types of therapies (anti-IgE, anti-eosinophil, anti-IL4). Biomarkers help to identify type-2 severe asthma but total IgE, sIgE, blood eosinophil, and FeNO are not enough to select 1 specific therapy. With the increasing arrival of new biological therapies, it is necessary to identify new biomarkers that allow us to improve our selection criteria for the best therapy for each patient or to construct a prediction rule.