Department of Pediatrics, Seoul National University College of Medicine, Seoul, South Korea.
Department of Pediatrics, Korea University College of Medicine, Seoul, South Korea.
BMC Pulm Med. 2019 Mar 15;19(1):64. doi: 10.1186/s12890-019-0829-3.
Asthma is a syndrome composed of heterogeneous disease entities. Although it is agreed that proper asthma endo-typing and appropriate type-specific interventions are crucial in the management of asthma, little data are available regarding pediatric asthma.
We designed a cluster-based, prospective, observational cohort study of asthmatic children in Korea (Korean childhood Asthma Study [KAS]). A total of 1000 Korean asthmatic children, aged from 5 to 15 years, will be enrolled at the allergy clinics of the 19 regional tertiary hospitals from August 2016 to December 2018. Physicians will verify the relevant histories of asthma and comorbid diseases, as well as airway lability from the results of spirometry and bronchial provocation tests. Questionnaires regarding subjects' baseline characteristics and their environment, self-rating of asthma control, and laboratory tests for allergy and airway inflammation will be collected at the time of enrollment. Follow-up data regarding asthma control, lung function, and environmental questionnaires will be collected at least every 6 months to assess outcome and exacerbation-related aggravating factors. In a subgroup of subjects, peak expiratory flow rate will be monitored by communication through a mobile application during the overall study period. Cluster analysis of the initial data will be used to classify Korean pediatric asthma patients into several clusters; the exacerbation and progression of asthma will be assessed and compared among these clusters. In a subgroup of patients, big data-based deep learning analysis will be applied to predict asthma exacerbation.
Based on the assumption that asthma is heterogeneous and each subject exhibits a different subset of risk factors for asthma exacerbation, as well as a different disease progression, the KAS aims to identify several asthma clusters and their essential determinants, which are more suitable for Korean asthmatic children. Thereafter we may suggest cluster-specific strategies by focusing on subjects' personalized aggravating factors during each exacerbation episode and by focusing on disease progression. The KAS will provide a good academic background with respect to each interventional strategy to achieve better asthma control and prognosis.
哮喘是一种由异质性疾病实体组成的综合征。尽管人们一致认为适当的哮喘内型分型和针对特定类型的干预措施对于哮喘的管理至关重要，但关于儿科哮喘的数据很少。
我们在韩国进行了一项基于聚类的、前瞻性、观察性队列研究，纳入了哮喘患儿（韩国儿童哮喘研究[KAS]）。2016 年 8 月至 2018 年 12 月，在 19 家区域三级医院的过敏诊所共纳入 1000 例年龄 5 至 15 岁的韩国哮喘患儿。医生将从肺功能检查和支气管激发试验的结果中验证哮喘和合并症的相关病史以及气道不稳定性。在入组时，将收集有关受试者基线特征及其环境、哮喘控制自我评估以及过敏和气道炎症实验室检查的问卷。在整个研究期间，将至少每 6 个月收集一次关于哮喘控制、肺功能和环境问卷的随访数据，以评估结果和加重因素。在亚组受试者中，将通过移动应用程序进行通讯来监测呼气峰流速。将对初始数据进行聚类分析，将韩国儿科哮喘患者分为几个亚组；将在这些亚组中评估和比较哮喘的加重和进展。在亚组患者中，将应用基于大数据的深度学习分析来预测哮喘加重。
基于哮喘是异质性的，每个患者都表现出不同的哮喘加重风险因素亚集和不同的疾病进展的假设，KAS 旨在确定几个哮喘亚组及其基本决定因素，这些亚组更适合韩国哮喘儿童。此后，我们可以根据每个加重发作期间患者的个性化加重因素和疾病进展情况，建议针对亚组的策略。KAS 将为每个干预策略提供良好的学术背景，以实现更好的哮喘控制和预后。
