目的系统评价孟鲁司特治疗成人哮喘急性发作的疗效和安全性。方法计算机检索Pubmed、Embase、Web of Science、OVID和Cochrane图书馆等电子数据库,查找应用孟鲁司特与安慰剂治疗成人哮喘急性发作期患者的随机对照试验(RCT)。对符合条件的RCT,由2名研究者独立进行资料提取和质量评价,采用RevMan 5.1软件进行Meta分析,采用GRADE指南对证据质量和等级推荐进行分级,计算相关临床结局的需要处理的例数(NNT)。结果共纳入5个RCT(n=947)的成人哮喘急性发作患者。Meta分析结果显示,与安慰剂比较,孟鲁司特能明显改善哮喘急性发作的呼气峰流速(MD=10.65[2.81,18.49],P=0.008)和减少全身糖皮质激素的使用(RR=0.75[0.62,0.92],NNT=7[4,46],P=0.005),但在减少住院治疗(RR=0.78[0.57,1.06],NNT=19[9,+∞],P=0.110)及治疗失败(RR=0.85[0.67,1.09],NNT=17[9,+∞],P=0.314)方面差异无统计学意义。GRADE证据级别及推荐强度结果显示,证据水平为低～中等,推荐等级为弱推荐。结论孟鲁司特能改善哮喘急性发作时的肺功能,且可减少口服糖皮质激素使用,而有关减少住院治疗和治疗失败的临床疗效有待进一步研究。
Background Asthma is a heterogeneous disease for which a strong genetic basis has been firmly established. Until now no studies have been undertaken to systemically explore the network of asthma-related genes using an internally developed literature-based discovery approach. This study was to explore asthma-related genes by using literature- based mining and network centrality analysis. Methods Literature involving asthma-related genes were searched in PubMed from 2001 to 2011. Integration of natural language processing with network centrality analysis was used to identify asthma susceptibility genes and their interaction network. Asthma susceptibility genes were classified into three functional groups by gene ontology （GO） analysis and the key genes were confirmed by establishing asthma-related networks and pathways. Results Three hundred and twenty-six genes related with asthma such as IGHE （IgE）, interleukin （IL）-4, 5, 6, 10, 13, 17A, and tumor necrosis factor （TNF）-alpha were identified. GO analysis indicated some biological processes （developmental processes, signal transduction, death, etc.）, cellular components （non-structural extracellular, plasma membrane and extracellular matrix）, and molecular functions （signal transduction activity） that were involved in asthma. Furthermore, 22 asthma-related pathways such as the Toll-like receptor signaling pathway, hematopoietic cell lineage, JAK-STAT signaling pathway, chemokine signaling pathway, and cytokine-cytokine receptor interaction, and 17 hub genes, such as JAK3, CCR1-3, CCR5-7, CCR8, were found. Conclusions Our study provides a remarkably detailed and comprehensive picture of asthma susceptibility genes and their interacting network. Further identification of these genes and molecular pathways may play a prominent role in establishing rational therapeutic approaches for asthma.
Background The performance of asthma control test （ACT） at baseline for predicting future risk of asthma exacerbation has not been previously demonstrated. This study was designed to explore the ability of the baseline ACT score to predict future risk of asthma exacerbation during a 12-month follow-up. Methods This post hoc analysis included data from a 12-month prospective cohort study in patients with asthma （n=290）. The time to the first asthma exacerbation was analyzed and the association between baseline ACT scores and future risk of asthma exacerbation was calculated as adjusted odds ratio （OR） using Logistic regression models. Further, sensitivity and specificity were estimated at each cut-point of ACT scores for predicting asthma exacerbations. Results The subjects were divided into three groups, which were uncontrolled （U, n=128）, partly-controlled （PC, n=111）, and well controlled （C, n=51） asthma. After adjustment, the decreased ACT scores at baseline in the U and PC groups were associated with an increased probability of asthma exacerbations （OR 3.65 and OR 5.75, respectively）, unplanned visits （OR 8.03 and OR 8.21, respectively） and emergency visits （OR 20.00 and OR 22.60, respectively） over a 12-month follow-up period. The time to the first asthma exacerbation was shorter in the groups with U and PC asthma （all P 〈0.05）. The baseline ACT of 20 identified as the cut-point for screening the patients at high risk of asthma exacerbations had an increased sensitivity of over 90.0% but a lower specificity of about 30.0%. Conclusion Our findings indicate that the baseline ACT score with a high sensitivity could rule out patients at low risk of asthma exacerbations and predict future risk of asthma exacerbations in clinical practice.
WEI Hua-huaZHOU TingWANG LanZHANG Hong-pingFU Juan-juanWANG LeiJI Yu-linWANG Gang
