Cost-effectiveness of chest radiography using artificial intelligence for lung cancer screening in South Korea.
Authors
Affiliations (8)
Affiliations (8)
- Department of Biohealth Industry, Graduate School of Transdisciplinary Health Sciences, Yonsei University, Seoul, Republic of Korea.
- Division of Tourism and Wellness, Hankuk University of Foreign Studies (HUFS), Yongin, Republic of Korea.
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Translational-Transdisciplinary Research Center, Clinical Research Institute, Kyung Hee University, Seoul, Republic of Korea.
- Department of Orthopedic Surgery, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
- Department of Otorhinolaryngology, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
- Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
- Yonsei Institute for Digital Health, Yonsei University, 50-1, Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. [email protected].
Abstract
Artificial intelligence (AI) shows promise in improving the accuracy and efficiency of lung cancer screening, but its economic value remains uncertain. We developed a decision-analytic model combining a decision tree and Markov model to evaluate five screening strategies in South Korea: no screening, chest X-ray (CXR), AI-assisted CXR, low-dose computed tomography (LDCT), and AI-assisted LDCT. We simulated hypothetical cohorts of 10,000 individuals, stratified by age group and smoking status to reflect the Korean population distribution, and projected their lifetime costs and quality-adjusted life years (QALYs). Analyses applied a 4.5% discount rate and a willingness-to-pay (WTP) threshold of $32,409.9 per QALY. AI-assisted CXR produced incremental cost-effectiveness ratio (ICER) of $8679-$10,030 per QALY, demonstrating cost-effectiveness across all age groups. CXR alone was less favorable, and LDCT-based strategies exceeded the willingness-to-pay (WTP) threshold. These findings suggest AI-assisted CXR offers a scalable, economically viable strategy for lung cancer screening, supporting its integration into national programs.