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.
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.
摘要：
背景：本研究旨在评估呼出气一氧化氮（FeNO）联合肺功能检测（PFT）预测接受dupilumab治疗的重度哮喘患者治疗结果的有效性。
方法：本研究共纳入2022年1月至2023年6月我院就诊的31例重度哮喘患者，28例患者完成了为期16周的dupilumab疗程。基线临床数据，包括人口统计信息，血嗜酸性粒细胞计数,血清IgE水平，FeNO,哮喘控制测试（ACT），哮喘控制问卷（ACQ），和其他参数，被收集。建立了使用广义线性模型的预测模型。
结果：在dupilumab治疗16周疗程后，22例患者根据GETE评分显示有效反应，而6名患者是无应答者。值得注意的是,临床参数如血液嗜酸性粒细胞计数显著改善，血清IgE水平，FeNO,FEV1,FEV1%,ACT,和ACQ在两个应答组(p<0.05)。FeNO和肺功能检查显示AUC值分别为0.530、0.561和0.765，在预测dupilumab的临床疗效时，低于FeNO与FEV1%结合时。FeNO和FEV1%联合预测治疗反应的敏感性为1.000,特异性为0.591。
结论：FeNO和FEV1%的联合评估为预测dupilumab治疗严重哮喘的临床疗效提供了更高的准确性。然而,需要进一步开展具有全面随访数据的更大规模临床研究,以验证不同患者人群的治疗效果和适用性.
方法：本研究共纳入2022年1月至2023年6月我院就诊的31例重度哮喘患者，28例患者完成了为期16周的dupilumab疗程。基线临床数据，包括人口统计信息，血嗜酸性粒细胞计数,血清IgE水平，FeNO,哮喘控制测试（ACT），哮喘控制问卷（ACQ），和其他参数，被收集。建立了使用广义线性模型的预测模型。
结果：在dupilumab治疗16周疗程后，22例患者根据GETE评分显示有效反应，而6名患者是无应答者。值得注意的是,临床参数如血液嗜酸性粒细胞计数显著改善，血清IgE水平，FeNO,FEV1,FEV1%,ACT,和ACQ在两个应答组(p<0.05)。FeNO和肺功能检查显示AUC值分别为0.530、0.561和0.765，在预测dupilumab的临床疗效时，低于FeNO与FEV1%结合时。FeNO和FEV1%联合预测治疗反应的敏感性为1.000,特异性为0.591。
结论：FeNO和FEV1%的联合评估为预测dupilumab治疗严重哮喘的临床疗效提供了更高的准确性。然而,需要进一步开展具有全面随访数据的更大规模临床研究,以验证不同患者人群的治疗效果和适用性.
