Section of Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, 1504 Taub Loop, Houston, TX, 77030, USA.
Section of Pulmonary, Critical Care and Sleep Medicine, Baylor College of Medicine, 6620 Main Street, MS: BCM621, Houston, TX, 77030, USA.
Curr Allergy Asthma Rep. 2017 Sep 19;17(10):69. doi: 10.1007/s11882-017-0739-5.
Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma.
Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.
哮喘是一种具有多种表型的异质性疾病。严重疾病患者的治疗具有挑战性。预测生物标志物是可衡量的特征，反映了哮喘的潜在病理生理学，并可以识别可能对特定治疗有反应的患者。这篇综述讨论了哮喘中预测生物标志物的最新知识。
最近评估针对 IgE、IL-5、IL-13 和 IL-4 的生物疗法的试验利用预测生物标志物来识别可能从治疗中受益的患者。其他研究表明，使用复合生物标志物可能在调整哮喘治疗方面提供更好的预测能力。多种生物标志物，包括痰嗜酸性粒细胞计数、血液嗜酸性粒细胞计数、呼气中一氧化氮的分数浓度（FeNO）和血清骨膜蛋白，已被用于识别哪些患者将对靶向哮喘药物有反应。需要进一步的工作将预测生物标志物整合到临床实践中。
