Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea. - 2026
Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea.
Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiograhs in South Korea.pdf
artificial intelligence; chest radiographs; cost-effectiveness; osteoporosis; screening; Endocrinology, Diabetes and Metabolism; Orthopedics and Sports Medicine
Abstract :
[en] South Korea, now a "super-aged" society, faces a rising burden of fragility fractures, yet underdiagnosis remains a major barrier, with limited DXA access restricting early detection. Artificial intelligence (AI) applied to routine chest radiographs enables opportunistic screening. In March 2025, Osteo Signal, a deep learning model developed in the South Korean population, received regulatory approval for use in both men and women. Unlike prior evaluations in women only, this study assessed its cost-effectiveness in adults aged ≥50 yr of both sexes. A model estimated the cost per quality-adjusted life year (QALY) gained (2025 Korean Won, KRW) from opportunistic AI-assisted chest radiograph screening vs no screening. Model inputs included osteoporosis prevalence (fixed prevalence: 37% in women and 7.5% in men and age-specific prevalence), diagnostic performance of Osteo Signal, and realistic probabilities of DXA confirmation, treatment initiation, and medication persistence. Patients were assumed to receive alendronate or denosumab. Analyses were performed in the overall population and by sex. In the fixed-prevalence scenario, screening improved outcomes, preventing 46 fractures, gaining 21 life years and 36 QALYs per 10 000 adults, while increasing treatment expenditures. The incremental cost-effectiveness ratio (ICER) was KRW 12 096 960 (~USD 8650) per QALY in the overall population, below South Korea's willingness-to-pay threshold (KRW 30 million). Subgroup ICERs were KRW 8 910 449 for women and KRW 44 746 862 for men. In the age-specific prevalence scenario, the ICERs were KRW 7 473 124 for the overall population, KRW 4 941 078 for women, and KRW 30 006 944 for men. Artificial intelligence-enhanced chest radiograph screening is cost-effective for South Korean adults aged ≥50 yr when evaluated across both men and women. While sex-specific differences exist, the combined analysis highlights meaningful population-level value, supporting adoption to reduce the national burden of osteoporosis and fractures.
Disciplines :
Public health, health care sciences & services
Author, co-author :
Hiligsmann, Mickaël ; Université de Liège - ULiège > Département des sciences de la santé publique > Santé publique, Epidémiologie et Economie de la santé ; Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, 6200 MD, The Netherlands
Kong, Sung Hye ; Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Gyeonggi-do 13620, Republic of Korea
Alokail, Majed; Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh 11453, Saudi Arabia
Kim, Mi-Young; Department of Internal Medicine, Madeulsoo Internal Medicine Clinic, Seoul 01678, Republic of Korea ; Medical Affairs, Promedius Inc., Seoul 05510, Republic of Korea
Reginster, Jean-Yves ; Université de Liège - ULiège > Département des sciences de la santé publique ; Protein Research Chair, Biochemistry Department, College of Science, King Saud University, Riyadh 11453, Saudi Arabia
Language :
English
Title :
Evaluating the cost-effectiveness of artificial intelligence-enhanced osteoporosis screening in men and women using routine chest radiographs in South Korea.
A research grant was received from Promedius partially covering the cost related to this study. The funder had no access to the dataset and model, and had no role in study design, data collection, or analysis. This work was partly supported by the Distinguished Scientist Fellowship Program (DSFP) of the King Saud University, Riyadh, Kingdom of Saudi Arabia.M.H. has received research grants (paid to institution) from Radius Health, and Angelini Pharma, lecture fees from IBSA (paid to institution) and Echolight, and was grant advisor for Pfizer (paid to institution) and consultant (paid to institution) for Gr\u00FCnenthal.
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