Endoscopic gastric cancer screening in Korea

The Korean National Cancer Screening Program (NCSP) for gastric cancer, launched in 1999, has contributed significantly to reducing gastric cancer mortality. The program currently provides biennial upper endoscopy or UGI series for individuals aged 40 and older. Nationwide data demonstrate that repeated participation in endoscopic screening is associated with a substantial reduction in gastric cancer mortality--up to 47% among those screened three times or more. These findings underscore the critical role of organized endoscopic screening in early detection and improved survival outcomes. Over the past two decades, the program has evolved with improvements in participation rates, quality control, and guideline updates. However, several challenges remain. With the gradual decline in Helicobacter pylori infection rates and the overall incidence of gastric cancer, there is increasing concern about over-screening, unnecessary biopsies, and socioeconomic burden. Additionally, the current "one-size-fits-all" approach, which lacks upper age limits and risk stratification, may not be sustainable or efficient in the long term. To address these issues, a transition toward a more personalized screening strategy is warranted. Future programs should incorporate individual risk factors such as H. pylori infection, atrophic gastritis, and intestinal metaplasia to tailor the screening interval, initiation, and termination age. Furthermore, efforts to improve the quality and standardization of endoscopic procedures will be essential. Integrating artificial intelligence (AI) into gastric cancer screening holds great promise. AI-assisted endoscopy can enhance lesion detection, reduce inter-observer variability, and support risk-based decision-making, thereby contributing to the overall effectiveness and efficiency of the screening process. In summary, the Korean NCSP has demonstrated a substantial impact in reducing gastric cancer mortality through endoscopic screening. Moving forward, the focus should shift toward risk-based, ersonalized screening models, with AI expected to play an increasingly important role in improving screening quality and outcomes.