Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, Postbus 85500, 3508GA Utrecht, The Netherlands.
JAMA. 2011 Oct 26;306(16):1775-81. doi: 10.1001/jama.2011.1531.
Smoking is a major risk factor for both cancer and chronic obstructive pulmonary disease (COPD). Computed tomography (CT)-based lung cancer screening may provide an opportunity to detect additional individuals with COPD at an early stage.
To determine whether low-dose lung cancer screening CT scans can be used to identify participants with COPD.
DESIGN, SETTING, AND PATIENTS: Single-center prospective cross-sectional study within an ongoing lung cancer screening trial. Prebronchodilator pulmonary function testing with inspiratory and expiratory CT on the same day was obtained from 1140 male participants between July 2007 and September 2008. Computed tomographic emphysema was defined as percentage of voxels less than -950 Hounsfield units (HU), and CT air trapping was defined as the expiratory:inspiratory ratio of mean lung density. Chronic obstructive pulmonary disease was defined as the ratio of forced expiratory volume in the first second to forced vital capacity (FEV(1)/FVC) of less than 70%. Logistic regression was used to develop a diagnostic prediction model for airflow limitation.
Diagnostic accuracy of COPD diagnosis using pulmonary function tests as the reference standard.
Four hundred thirty-seven participants (38%) had COPD according to lung function testing. A diagnostic model with CT emphysema, CT air trapping, body mass index, pack-years, and smoking status corrected for overoptimism (internal validation) yielded an area under the receiver operating characteristic curve of 0.83 (95% CI, 0.81-0.86). Using the point of optimal accuracy, the model identified 274 participants with COPD with 85 false-positives, a sensitivity of 63% (95% CI, 58%-67%), specificity of 88% (95% CI, 85%-90%), positive predictive value of 76% (95% CI, 72%-81%); and negative predictive value of 79% (95% CI, 76%-82%). The diagnostic model showed an area under the receiver operating characteristic curve of 0.87 (95% CI, 0.86-0.88) for participants with symptoms and 0.78 (95% CI, 0.76-0.80) for those without symptoms.
Among men who are current and former heavy smokers, low-dose inspiratory and expiratory CT scans obtained for lung cancer screening can identify participants with COPD, with a sensitivity of 63% and a specificity of 88%.
吸烟是癌症和慢性阻塞性肺疾病（COPD）的主要危险因素。基于计算机断层扫描（CT）的肺癌筛查可能提供机会，以便在早期发现更多患有 COPD 的个体。
确定低剂量肺癌筛查 CT 扫描是否可用于识别 COPD 患者。
设计、地点和患者：在一项正在进行的肺癌筛查试验中，进行了一项单中心前瞻性横断面研究。2007 年 7 月至 2008 年 9 月期间，对 1140 名男性参与者进行了同日的预支气管扩张剂肺功能检测，包括吸气和呼气 CT。CT 肺气肿定义为小于-950 豪斯菲尔德单位（HU）的体素百分比，CT 空气潴留定义为平均肺密度的呼气相/吸气相比值。慢性阻塞性肺疾病定义为第一秒用力呼气量与用力肺活量（FEV1/FVC）的比值小于 70%。采用 logistic 回归方法建立气流受限的诊断预测模型。
以肺功能测试为参考标准，评估 COPD 诊断的准确性。
根据肺功能测试，437 名参与者（38%）患有 COPD。采用 CT 肺气肿、CT 空气潴留、体重指数、吸烟年数和校正了过拟合的吸烟状态的诊断模型（内部验证），其受试者工作特征曲线下面积为 0.83（95%置信区间，0.81-0.86）。使用最佳准确性点，该模型识别出 274 名 COPD 患者，有 85 例假阳性，敏感性为 63%（95%置信区间，58%-67%），特异性为 88%（95%置信区间，85%-90%），阳性预测值为 76%（95%置信区间，72%-81%）；阴性预测值为 79%（95%置信区间，76%-82%）。对于有症状的参与者，诊断模型的受试者工作特征曲线下面积为 0.87（95%置信区间，0.86-0.88），对于无症状的参与者为 0.78（95%置信区间，0.76-0.80）。
在目前和曾经大量吸烟的男性中，用于肺癌筛查的低剂量吸气和呼气 CT 扫描可识别 COPD 患者，其敏感性为 63%，特异性为 88%。
