Gallardo-Estrella Leticia, Pompe Esther, de Jong Pim A, Jacobs Colin, van Rikxoort Eva M, Prokop Mathias, Sánchez Clara I, van Ginneken Bram
Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.
Department of Respiratory Medicine, University Medical Center Utrecht, Utrecht, the Netherlands.
PLoS One. 2017 Dec 11;12(12):e0188902. doi: 10.1371/journal.pone.0188902. eCollection 2017.
The purpose of this study is to develop a computed tomography (CT) biomarker of emphysema that is robust across reconstruction settings, and evaluate its ability to predict mortality in patients at high risk for lung cancer. Data included baseline CT scans acquired between August 2002 and April 2004 from 1737 deceased subjects and 5740 surviving controls taken from the National Lung Screening Trial. Emphysema scores were computed in the original scans (origES) and after applying resampling, normalization and bullae analysis (normES). We compared the prognostic value of normES versus origES for lung cancer and all-cause mortality by computing the area under the receiver operator characteristic curve (AUC) and the net reclassification improvement (NRI) for follow-up times of 1-7 years. normES was a better predictor of mortality than origES. The 95% confidence intervals for the differences in AUC values indicated a significant difference for all-cause mortality for 2 through 6 years of follow-up, and for lung cancer mortality for 1 through 7 years of follow-up. 95% confidence intervals in NRI values showed a statistically significant improvement in classification for all-cause mortality for 2 through 7 years of follow-up, and for lung cancer mortality for 3 through 7 years of follow-up. Contrary to conventional emphysema score, our normalized emphysema score is a good predictor of all-cause and lung cancer mortality in settings where multiple CT scanners and protocols are used.
本研究的目的是开发一种在不同重建设置下均稳定可靠的肺气肿计算机断层扫描（CT）生物标志物，并评估其预测肺癌高危患者死亡率的能力。数据包括2002年8月至2004年4月期间从国家肺癌筛查试验中获取的1737名已故受试者和5740名存活对照的基线CT扫描。在原始扫描（origES）以及应用重采样、归一化和肺大疱分析后（normES）计算肺气肿评分。我们通过计算1至7年随访期的受试者工作特征曲线下面积（AUC）和净重新分类改善（NRI），比较了normES与origES对肺癌和全因死亡率的预后价值。normES比origES是更好的死亡率预测指标。AUC值差异的95%置信区间表明，随访2至6年的全因死亡率以及随访1至7年的肺癌死亡率存在显著差异。NRI值的95%置信区间显示，随访2至7年的全因死亡率以及随访3至7年的肺癌死亡率在分类上有统计学显著改善。与传统肺气肿评分相反，我们的归一化肺气肿评分在使用多种CT扫描仪和方案的情况下是全因和肺癌死亡率的良好预测指标。
