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Development of an Empirically Calibrated Model of Gastric Cancer in Two High-Risk Countries

¹ Program in Health Decision Science, Department of Health Policy and Management and ² Department of Population and International Health and Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts; ³ Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, Minnesota; and ⁴ Institute of Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts

Requests for reprints: Jennifer M. Yeh, Program in Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, 718 Huntington Avenue, 2nd Floor, Boston, MA 02115. Phone: 617-432-4385; Fax: 617-432-0190. E-mail: jyeh{at}hsph.harvard.edu

Although epidemiologic studies have established the relationship between Helicobacter pylori and gastric cancer and promising results that H. pylori treatment can reduce cancer incidence among individuals without preexisting precancerous lesions, there is no consensus on whether screening for H. pylori should be conducted. Our objective was to synthesize the available data to develop and empirically calibrate a mathematical model of gastric cancer and H. pylori in China and Colombia that could be used to provide qualitative insight into the benefits and cost-effectiveness of primary and secondary gastric cancer prevention strategies. The model represents the natural history of noncardia intestinal type gastric adenocarcinomas as a sequence of transitions among health states (e.g., normal gastric mucosa, chronic nonatrophic gastritis, gastric atrophy, intestinal metaplasia, dysplasia, and gastric cancer) stratified by H. pylori status. Initial plausible ranges for each parameter were established using data from published literature. A likelihood-based empirical calibration approach was used to identify multiple good-fitting parameter sets that were consistent with epidemiologic data. We then used these parameter sets to estimate a range of likely outcomes associated with H. pylori screening. This modeling approach allows for parameter uncertainty surrounding the natural history of H. pylori and gastric cancer to be reflected in the results of comparative analyses of different gastric cancer prevention strategies. As better data become available, the model can be refined and recalibrated, and, as such, be used as an iterative tool to assess the likely health and economic outcomes associated with gastric cancer prevention strategies. (Cancer Epidemiol Biomarkers Prev 2008;17(5):1179–87)