Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China.
Department of Pulmonary and Critical Care Medicine, National Regional Center for Respiratory Medicine, Jiangxi hospital of China-Japan Friendship Hospital, Nanchang, China.
Ther Adv Respir Dis. 2023 Jan-Dec;17:17534666231170821. doi: 10.1177/17534666231170821.
To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab.
We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant laboratory examination results along with case records of omalizumab treatment responsiveness after 16 weeks. We compared the differences in variables between the group of patients that responded to omalizumab therapy and the non-responder group, and then performed univariate and multivariate logistic regression. Finally, we analyzed the difference in response rate for subgroups by selecting cut-off values for the variables using Fisher's exact probability method.
This retrospective, single-center observational study enrolled 32 patients with severe asthma who were prescribed daily high-dose inhaled corticosteroids and long-acting β2 receptor agonists on long-acting muscarinic receptor antagonists with or without OCS. Data on age, sex, BMI, bronchial thermoplasty, FeNO, serum total IgE, FEV1, blood eosinophils, induced sputum eosinophils, blood basophils, and complications were not significantly different between the responder and non-responder groups. In the univariate and multivariate logistic regression, all the variants were not significant, and we were unable to build a regression model. We used normal high values and the mean or median of variables as cut-off values to create patient subgroups for the variables and found no significant difference in the omalizumab response rate between the subgroups.
The responsiveness of omalizumab is not associated with pretreatment clinical biomarkers, and these biomarkers should not be used to predict the responsiveness of omalizumab.
探索基线临床生物标志物和特征是否可用于预测奥马珠单抗的应答反应。
我们回顾性分析了一组接受奥马珠单抗治疗的重度哮喘患者，收集了他们的基线数据和相关实验室检查结果以及奥马珠单抗治疗 16 周后的应答病例记录。我们比较了应答组和无应答组患者之间变量的差异，然后进行了单变量和多变量逻辑回归。最后，我们使用 Fisher 精确概率法选择变量的截止值，对亚组的应答率进行分析。
这项回顾性、单中心观察性研究纳入了 32 名接受每日高剂量吸入皮质激素和长效β2 受体激动剂治疗的重度哮喘患者，这些患者长期使用长效毒蕈碱受体拮抗剂，同时或不使用 OCS。应答组和无应答组患者的年龄、性别、BMI、支气管热成形术、FeNO、血清总 IgE、FEV1、血嗜酸粒细胞、诱导痰嗜酸粒细胞、血嗜碱性粒细胞和并发症等数据无显著差异。在单变量和多变量逻辑回归中，所有变量均无显著差异，我们无法建立回归模型。我们使用正常高值和变量的均值或中位数作为截止值，为变量创建患者亚组，发现亚组之间奥马珠单抗的应答率无显著差异。
奥马珠单抗的应答反应与治疗前的临床生物标志物无关，这些标志物不应用于预测奥马珠单抗的应答反应。
