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识别预测全因死亡率的慢性阻塞性肺疾病轴:COPDGene 研究。

Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study.

机构信息

Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado.

Department of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, Colorado.

出版信息

Am J Epidemiol. 2018 Oct 1;187(10):2109-2116. doi: 10.1093/aje/kwy087.

Abstract

Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.

摘要

慢性阻塞性肺疾病(COPD)是一种由肺部损伤引起的综合征,导致肺功能下降和结构完整性受损。肺功能测试(PFT)用于诊断和分层 COPD 严重程度分组,胸部计算机断层扫描(CT)成像常用于评估肺部的结构变化。我们假设,与单独使用 PFT 相比,PFT 和 CT 表型的结合将为评估 COPD 与肺功能相关的潜在形态差异提供更强大的工具。我们使用 26 个变量的因子分析对 2008 年 1 月至 2011 年 6 月期间在美国 21 个临床中心招募的 8157 名 COPDGene 队列参与者进行分类。这些因素被用于使用 Cox 比例风险建模预测全因死亡率。五个因素解释了 80%的协方差,代表了以下领域:因子 1,肺气肿增加和肺功能下降;因子 2,气道疾病和肺功能下降;因子 3,气体潴留;因子 4,CT 变异性;因子 5,过度充气。在超过 46079 人年的随访后,因素 1 至 4 与死亡率相关,并且因素 1 和 2 之间存在显著的协同交互作用。在 COPD 的评估中,考虑 CT 测量与 PFT 可以识别出死亡风险特别高的患者。

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