Agache Ioana, Rogozea Liliana
Faculty of Medicine, Department of Allergy and Clinical Immunology, Transylvania University of Brasov, Brasov, Romania.
Allergy Asthma Immunol Res. 2017 Nov;9(6):466-476. doi: 10.4168/aair.2017.9.6.466.
Measurement of biomarkers has been incorporated within clinical research of asthma to characterize the population and to associate the disease with environmental and therapeutic effects. Regrettably, at present, there are no specific biomarkers, none is validated or qualified, and endotype-driven choices overlap. Biomarkers have not yet reached clinical practice and are not included in current asthma guidelines. Last but not least, the choice of the outcome upholding the value of the biomarkers is extremely difficult, since it has to reflect the mechanistic intervention while being relevant to both the disease and the particular person. On the verge of a new age of asthma healthcare standard, we must embrace and adapt to the key drivers of change. Disease endotypes, biomarkers, and precision medicine represent an emerging model of patient care building on large-scale biologic databases, omics and diverse cellular assays, health information technology, and computational tools for analyzing sizable sets of data. A profound transformation of clinical and research pattern from population to individual risk and from investigator-imposed subjective disease clustering (hypothesis driven) to unbiased, data-driven models is facilitated by the endotype/biomarker-driven approach.
生物标志物的测量已被纳入哮喘临床研究中，以对人群进行特征描述，并将该疾病与环境及治疗效果联系起来。遗憾的是，目前尚无特异性生物标志物，没有一个经过验证或具备资质，且基于内型的选择相互重叠。生物标志物尚未应用于临床实践，也未被纳入现行哮喘指南。最后但同样重要的是，要选择能够支持生物标志物价值的结果极为困难，因为它必须反映机制性干预，同时又要与疾病及特定个体相关。在哮喘医疗保健标准新时代即将来临之际，我们必须接受并适应这些关键的变革驱动因素。疾病内型、生物标志物和精准医学代表了一种新兴的患者护理模式，其建立在大规模生物数据库、组学和多样的细胞检测、健康信息技术以及用于分析大量数据集的计算工具基础之上。内型/生物标志物驱动的方法推动了临床和研究模式从群体风险向个体风险、从研究者主观设定的疾病聚类（假设驱动）向无偏倚的、数据驱动模型的深刻转变。
