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在国家肺癌筛查试验中低剂量 CT 的 ROC 曲线。

ROC curves for low-dose CT in the National Lung Screening Trial.

机构信息

Division of Cancer Prevention, National Cancer Institute.

出版信息

J Med Screen. 2013;20(3):165-8. doi: 10.1177/0969141313500666. Epub 2013 Aug 30.

Abstract

The National Lung Screening Trial (NLST) reported a 20% reduction in lung cancer specific mortality using low-dose chest CT (LDCT) compared with chest radiograph (CXR) screening. The high number of false positive screens with LDCT (around 25%) raises concerns. NLST radiologists reported LDCT screens as either positive or not positive, based primarily on the presence of a 4+ mm non-calcified lung nodule (NCN). They did not explicitly record a propensity score for lung cancer. However, by using maximum NCN size, or alternatively, radiologists' recommendations for diagnostic follow-up categorized hierarchically, surrogate propensity scores (PSSZ and PSFR) were created. These scores were then used to compute ROC curves, which determine possible operating points of sensitivity versus false positive rate (1-Specificity). The area under the ROC curve (AUC) was 0.934 and 0.928 for PSFR and PSSZ, respectively; the former was significantly greater than the latter. With the NLST definition of a positive screen, sensitivity and specificity of LDCT was 93.1% and 76.5%, respectively. With cutoffs based on PSFR, a specificity of 92.4% could be achieved while only lowering sensitivity to 86.9%. Radiologists using LDCT have good predictive ability; the optimal operating point for sensitivity and specificity remains to be determined.

摘要

国家肺癌筛查试验(NLST)报告称,与胸部 X 光(CXR)筛查相比,低剂量 CT(LDCT)可降低 20%的肺癌特异性死亡率。LDCT 筛查的假阳性率较高(约 25%)令人担忧。NLST 放射科医生根据是否存在 4+ 毫米非钙化肺结节(NCN),将 LDCT 筛查报告为阳性或阴性。他们没有明确记录肺癌的倾向评分。然而,通过使用最大 NCN 大小,或者放射科医生的诊断随访建议进行分层分类,创建了替代倾向评分(PSSZ 和 PSFR)。然后,这些评分用于计算 ROC 曲线,以确定敏感性与假阳性率(1 特异性)的可能操作点。ROC 曲线下面积(AUC)分别为 PSFR 和 PSSZ 的 0.934 和 0.928;前者显著大于后者。使用 NLST 阳性筛查的定义,LDCT 的敏感性和特异性分别为 93.1%和 76.5%。基于 PSFR 的截断值,特异性可达到 92.4%,而敏感性仅降低至 86.9%。使用 LDCT 的放射科医生具有良好的预测能力;敏感性和特异性的最佳操作点仍有待确定。

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