Determinants of Clinical Remission in Dupilumab-Treated Severe Eosinophilic Asthma: A Real-World Retrospective Study

Background: Dupilumab, a monoclonal antibody targeting the IL-4/IL-13 receptor, has shown significant efficacy in improving asthma control and reducing exacerbations in patients with severe eosinophilic asthma. However, there is a lack of knowledge about real-world data on clinical remission rates and their predictors. Objective: This study aimed to evaluate clinical outcomes, remission rates, and predictive factors of remission in a real-life cohort of patients with severe eosinophilic asthma treated with dupilumab. Methods: We conducted a retrospective, bicentric, observational study including 52 patients with severe eosinophilic asthma treated with dupilumab. Clinical, functional, and biomarkers were assessed at baseline, 6 months, and 12 months. Statistical analyses included logistic regression to identify independent predictors of clinical remission. Results: After 12 months of treatment, 48.2% of patients achieved clinical remission. Dupilumab significantly improved asthma control and lung function (including FVC and FEF25–75), reduced exacerbation rates, and maintenance therapy. High blood eosinophil levels (>490 cells/µL), high FeNO levels (>25 ppb), a history of CRSwNP, and better baseline FEV1 were associated with asthma remission. Conversely, obesity (BMI > 30) and related comorbidities (such as GERD, OSAS, and hypertension) and bronchiectasis were associated with a lower likelihood of remission. Multivariate analysis confirmed higher baseline FEV1 (OR 2.94; IC 1.13–7.6), positive history of CRSwNP (OR 8.03; IC 1.41–45.5), and higher baseline blood eosinophils (OR 1.003 IC 1.001–1.006) as independent predictors of clinical remission. Conclusions: These results are in line with the known effectiveness of dupilumab in severe eosinophilic asthma and identified a history of CRSwNP, higher baseline FEV1, and elevated blood eosinophils as key predictors of clinical remission. These findings may contribute to a more personalized approach to treatment selection, emphasizing the importance of comorbidity assessment together with type 2 inflammation biomarkers. Further prospective studies are needed to validate these results.