Simulation Models in Gastric Cancer Screening: A Systematic Review

Area of Science:

• Oncology
• Public Health
• Health Economics

Background:

• Simulation models are crucial for evaluating cancer screening strategies alongside randomized controlled trials and cohort studies.
• Assessing the multifaceted effects of gastric cancer screening, including cost-effectiveness, mortality reduction, and early detection, is vital for public health policy.
• Helicobacter pylori testing and endoscopy are key screening methods evaluated in gastric cancer prevention.

Purpose of the Study:

• To systematically review and evaluate the effects of gastric cancer screening methods, specifically Helicobacter pylori testing and endoscopy, as assessed by simulation models.
• To analyze cost-effectiveness, mortality reduction, quality-adjusted life-years, and early-stage detection rates associated with these screening interventions.

Main Methods:

• A systematic literature review was conducted using PubMed and Web of Science databases.
• Evaluated studies employed simulation models, predominantly Markov models, to assess gastric cancer screening interventions.
• Key metrics included incremental cost-effectiveness ratios, quality-adjusted life-years, deaths prevented, life-years saved, and incidence reduction.

Main Results:

• Nineteen studies on gastric cancer screening simulation models were identified; 14 focused on H. pylori testing and 7 on endoscopy.
• All studies evaluated cost-effectiveness. Of the H. pylori studies, 13 showed cost-effectiveness, and 11 reported benefits beyond cost, such as life-years extension and earlier detection.
• Endoscopy screening studies (n=5) also demonstrated good cost-effectiveness, with four showing additional non-cost benefits.

Conclusions:

• Simulation models indicate that Helicobacter pylori screening is cost-effective for gastric cancer.
• Despite cost-effectiveness, H. pylori screening is not routinely recommended due to insufficient evidence of gastric cancer mortality reduction.
• Simulation modeling is recommended for planning cancer control strategies in Japan, emphasizing the need for rigorous examination of its future application.