External validation and comparison of the Brock model and Lung-RADS for the baseline lung cancer CT screening using data
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External validation and comparison of the Brock model and Lung-RADS for the baseline lung cancer CT screening using data from the Korean Lung Cancer Screening Project Hyungjin Kim 1,2 & Hyae Young Kim 3
&
Jin Mo Goo 1,2,4 & Yeol Kim 5
Received: 10 June 2020 / Revised: 8 September 2020 / Accepted: 12 November 2020 # European Society of Radiology 2020
Abstract Objectives To validate and compare the performance of the Brock model and Lung CT Screening Reporting and Data System (Lung-RADS) on nodules detected by baseline CT screening. Methods We performed a secondary analysis of the Korean Lung Cancer Screening Project (K-LUCAS; ClinicalTrials.gov, NCT03394703), a nationwide, multicenter, prospective cohort study. From April 2017 to December 2018, low-dose CT screening was performed on high-risk subjects. Discrimination and calibration of Brock models 2a and 2b (i.e., full model without and with spiculation, respectively) were assessed, and discrimination was compared with that of Lung-RADS, which utilized subjective assessment categories 2b (b stands for benign) and 4X. Results Of the 13,150 subjects, 4578 were eligible (median age 62 years; 4458 men; 9929 nodules including 40 lung cancers). Areas under the receiver operating characteristic curve were 0.96 (IQR 0.92–0.99) for Brock model 2a, 0.96 (IQR 0.92–0.99) for Brock model 2b, and 0.95 (IQR 0.91–0.99) for Lung-RADS (p = 0.32 and p = 0.34, respectively). At an equivalent cutoff of 5%, Brock model 2b (sensitivity 87.5% [35/40]; specificity 93.6% [9259/9889]; positive predictive value [PPV] 5.3% [35/665]; negative predictive value [NPV] 99.9% [9259/9264]) and Lung-RADS (sensitivity 87.5% [35/40]; specificity 93.3% [9222/9889]; PPV 5.0% [35/702]; NPV 99.9% [9222/9227]) performed similarly well (all p > 0.05). The calibration performance of both Brock models 2a and 2b was poor (both p < 0.001). Conclusions Lung-RADS, when reinforced with visual assessment–based categories, has a similar diagnostic performance to the Brock model for baseline CT scans. Key Points • Brock model 2b and Lung CT Screening Reporting and Data System (Lung-RADS) demonstrated a similar discrimination performance for lung cancer in the baseline CT screening (areas under the receiver operating characteristic curve 0.96 vs. 0.95; p = 0.34). • When visual assessment–based categories were removed from Lung-RADS, specificity and positive predictive value were lower than those of Brock model 2b (p = 0.001 and p = 0.02, respectively). • The Brock model showed poor calibration (p < 0.001). Keywords Diagnostic screening programs . Lung neoplasms . Statistical models . Multidetector computed tomography . Early detection of cancer
* Hyae Young Kim [email protected] 1
2
Department of Radiology, Seoul National University Hospital, 101, Daehak-ro, Jongno-gu, Seoul 03080, South Korea Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehak-ro, Jongno-gu, Seoul 03080, South Korea
3
Department of Diagnostic Radiology, National Cancer Center, 323, Ilsan-ro,
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