Yeh Jennifer M, Kuntz Karen M, Ezzati Majid, Hur Chin, Kong Chung Yin, Goldie Sue J
Program in Health Decision Science, Department of Health Policy and Management, Harvard School of Public Health, 718 Huntington Avenue, 2nd Floor, Boston, MA 02115, USA.
Cancer Epidemiol Biomarkers Prev. 2008 May;17(5):1179-87. doi: 10.1158/1055-9965.EPI-07-2539.
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.
尽管流行病学研究已证实幽门螺杆菌与胃癌之间的关系,且有前景的结果表明幽门螺杆菌治疗可降低无癌前病变个体的癌症发病率,但对于是否应进行幽门螺杆菌筛查尚无共识。我们的目标是综合现有数据,开发并通过实证校准中国和哥伦比亚的胃癌及幽门螺杆菌数学模型,该模型可用于定性洞察原发性和继发性胃癌预防策略的益处及成本效益。该模型将非贲门肠型胃腺癌的自然史表示为按幽门螺杆菌状态分层的健康状态(如正常胃黏膜、慢性非萎缩性胃炎、胃萎缩、肠化生、发育异常和胃癌)之间的一系列转变。使用已发表文献中的数据确定每个参数的初始合理范围。采用基于似然性的实证校准方法来识别与流行病学数据一致的多个拟合良好的参数集。然后,我们使用这些参数集来估计与幽门螺杆菌筛查相关的一系列可能结果。这种建模方法允许在不同胃癌预防策略的比较分析结果中反映围绕幽门螺杆菌和胃癌自然史的参数不确定性。随着更好的数据可用,该模型可以得到完善和重新校准,因此可作为一种迭代工具来评估与胃癌预防策略相关的可能健康和经济结果。