{Reference Type}: Journal Article
{Title}: Prediction of Clinical Response to Dupilumab in Patients with Severe Asthma Using Fractional Exhaled Nitric Oxide Combined with Pulmonary Function Testing.
{Author}: Liu YL;Zhang Y;
{Journal}: Int Arch Allergy Immunol
{Volume}: 185
{Issue}: 9
{Year}: 2024 Apr 30
{Factor}: 3.767
{DOI}: 10.1159/000538542
{Abstract}: BACKGROUND: This study aimed to assess the effectiveness of fractional exhaled nitric oxide (FeNO) combined with pulmonary function testing (PFT) for predicting the treatment outcome of patients with severe asthma receiving dupilumab.
METHODS: A total of 31 patients with severe asthma visiting our hospital from January 2022 to June 2023 were included in this study, with 28 patients completing a 16-week course of dupilumab treatment. Baseline clinical data, including demographic information, blood eosinophil counts, serum IgE levels, FeNO, asthma control test (ACT), asthma control questionnaire (ACQ), and other parameters, were collected. A predictive model using a generalized linear model was established.
RESULTS: Following the 16-week course of dupilumab treatment, 22 patients showed effective response based on GETE scores, while 6 patients were nonresponders. Notably, significant improvements were observed in clinical parameters such as blood eosinophil counts, serum IgE levels, FeNO, FEV1, FEV1%, ACT, and ACQ in both response groups (p < 0.05). FeNO and pulmonary function tests demonstrated AUC values of 0.530, 0.561, and 0.765, respectively, in predicting the clinical efficacy of dupilumab, which were lower than when FeNO was combined with FEV1%. The combination of FeNO and FEV1% had a sensitivity of 1.000 and specificity of 0.591 in predicting treatment response.
CONCLUSIONS: The combined assessment of FeNO and FEV1% provides improved accuracy for predicting the clinical efficacy of dupilumab in managing severe asthma. However, further larger scale clinical studies with comprehensive follow-up data are needed to validate the therapeutic efficacy and applicability across diverse patient populations.