Evaluating the Cost-Effectiveness of AI-Enhanced Osteoporosis Screening in Men and Women Using Routine Chest Radiographs in South Korea

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 versus no screening. Model inputs included osteoporosis prevalence (fixed prevalence: 37% in women, 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 12096960 (~USD 8650) per QALY in the overall population, below South Korea’s willingness-to-pay threshold (KRW 30 million). Subgroup ICERs were KRW 8910449 for women and KRW 44746862 for men. In the age-specific prevalence scenario, the ICERs were KRW 7473124 for the overall population, KRW 4941078 for women, and KRW 30006944 for men. AI-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.