One-off low-dose CT screening of positive nodules in lung cancer: A prospective community-based cohort study.

Background: To improve the early stage diagnosis and reduce the lung cancer (LC) mortality for positive nodule (PN) population, data on effectiveness of PN detection using one-off low-dose spiral computed tomography (LDCT) screening are needed to improve the PN management protocol. We evaluate the effectiveness of PN detection and developed a nomogram to predict LC risk for PNs.
Methods: A prospective, community-based cohort study was conducted. We recruited 292,531 eligible candidates during 2012-2018. Individuals at high risk of LC based on risk assessment underwent LDCT screening and were divided into PN and non-PN groups. The effectiveness of PN detection was evaluated in LC incidence, mortality, and all-cause mortality. We performed subgroup analysis of characteristic variables for the association between PN and LC risk. A competing risk model was used to develop the nomogram.
Results: Participants (n = 14901) underwent LDCT screening; PNs were detected in 1193 cases (8·0%). After a median follow-up of 6·1 years, 193 were diagnosed with LC (1·3%). Of these, 94 were in the PN group (8·0%). LC incidence, mortality, and all-cause mortality were significantly higher in the PN group (adjusted hazard ratios: 10.60 (7.91-14.20), 7.97 (5.20-12.20), and 1.94 (1.51-2.50), respectively). Additionally, various PN characteristics were associated with an increased probability of developing LC. The C-index value of the nomogram for predicting LC risk of PN individuals was 0·847.
Conclusions: The protocol of PNs management for improvement could focus on specific characteristic population and high-risk PN individuals by nomogram assessment.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)