The effect of different radiological models on diagnostic accuracy and lung cancer screening performance

Abstract

High false-positive (FP) scan rates associated with low-dose computed tomography (LDCT) lung cancer screening result in unnecessary follow-up tests and exposure to harm. The definition of a 'positive' scan can impact FP rates and screening performance. We explored the effect of Lung Imaging Reporting and Data System (Lung-RADS) criteria, PanCan Nodule Malignancy Probability Model and varying nodule size thresholds (≥4 mm, ≥6 mm, ≥8 mm) on diagnostic accuracy and screening performance compared with original trial definitions (National Lung Screening Trial (NLST) criteria) in a secondary analysis of a lung cancer screening cohort. We found Lung-RADS criteria and the PanCan Nodule Malignancy Probability Model could substantially improve screening performance and reduce FP scan rates compared with NLST definitions of positivity but that this needs to be balanced against possible risk of false-negative results.