RELATIONSHIP BETWEEN EFFECTIVENESS AND VARIATIVENESS OF BRONCHIAL ASTHMA MEDICATION WITH CLINICAL IMPROVEMENT OF BRONCHIAL ASTHMA

Abstract

Background: Bronchial asthma is a chronic inflammatory airway disease that is highly heterogeneous, both in terms of pathophysiology and response to therapy. The availability of various drug classes ranging from inhaled corticosteroids (ICS), bronchodilators, allergen immunotherapy (AIT), to various biologic agents does not necessarily guarantee uniform clinical improvement in every patient due to variability in endotypes, biomarkers, and treatment adherence. Objective: This review aims to analyze the relationship between the effectiveness and variability of various bronchial asthma drug classes with clinical improvement outcomes, including reduced exacerbations, improved lung function, and quality of life. Methods: A narrative literature review was compiled based on three main articles on allergen immunotherapy, targeted biologic therapy, and tezepelumab in severe asthma, supplemented by additional literature searches on therapy adherence and predictive biomarkers. Results and discussion: The effectiveness of conventional pharmacotherapy is strongly influenced by variability in patient adherence, with the average objective adherence to ICS ranging from 22 - 70% of the prescribed dose. Allergen immunotherapy has demonstrated consistent preventive and therapeutic effects in mild-moderate allergic asthma, but its benefits depend on dose, duration, and patient phenotype. Biologic therapy (anti-IgE, anti-IL-5/IL-5Rα, anti-IL-4Rα) significantly reduced exacerbations, particularly in the type 2-high phenotype with eosinophilia, while tezepelumab, a TSLP inhibitor, demonstrated efficacy across phenotypes, including type 2-low, with annual exacerbation reductions of up to 56–71%. This variability in response underscores the need for biomarker-guided approaches and combination therapies to optimize clinical improvement. Conclusion: The effectiveness of bronchial asthma medications is closely linked to the variability of disease endotypes, patient biomarkers, and therapy adherence; optimal clinical improvement is achieved through a personalized approach based on phenotypes and biomarkers, rather than a single, uniform treatment strategy.