Risk Prediction Model for Lung Cancer Screening
10.3348/jksr.2019.80.5.860
- Author:
Tae Jung KIM
1
;
Hyae Young KIM
;
Jin Mo GOO
;
Joo Sung SUN
Author Information
1. Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. taejung.kim1@gmail.com
- Publication Type:Review
- From:Journal of the Korean Radiological Society
2019;80(5):860-871
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
Lung cancer screening in high-risk subjects using low-dose CT can reduce mortality by 20%. Current evidence suggests that the development of a risk prediction model for lung cancer is one of the major advances in lung cancer screening. Herein, we review the technical requirements for evaluating different risk prediction models. Moreover, we describe the major lung cancer risk prediction models reported, and the results of lung cancer screening using these models.
