Comparative modeling of gastric cancer disparities and prevention in the US and globally

胃癌（GC），特别是胃腺癌，是第五大最常见的癌症和第三大最常见的癌症。 是全球癌症死亡的主要原因，被世界卫生组织列为被忽视的癌症。 Organization.在美国，有明显的差距，黑人，西班牙裔和亚洲人有近两个- 与白人相比，患GC或死于GC的风险增加一倍，反映了风险因素的差异，例如 幽门螺杆菌（H.幽门螺杆菌感染和吸烟，以及获得初级预防和护理。 有几个因素正在改变GC预防的前景，包括对该疾病的更好理解 自然史、前瞻性研究中关于预防的新证据以及随机化研究的预期结果 对照试验。由于早期GC检测可以通过允许治愈性手术或非侵入性治疗来提高生存率， 内镜切除术，新的胃癌预防靶向方法有可能显着改善 人口健康和减少GC的差距在美国虽然H。幽门螺杆菌一直是 迄今为止，全球GC预防工作中，H.美国的幽门螺杆菌患病率 世界已经强调了优化H的必要性。幽门螺杆菌筛查和治疗易受感染的 组一种方法是有针对性的内窥镜筛查高危人群。例如，被发现 胃肠道化生，一种与胃肠道疾病进展风险高相关的前驱病变， 在许多国家，建议对肿瘤进行内窥镜监测。迫切需要 确定有效和具有成本效益的战略，以解决这些临床挑战在美国，以及 全球范围内。这项拟议的工作建立在以前的GC工作跨越GC和H。pylori模拟模型 研究、GC二级数据库分析以及相关方法学和全球癌症建模 出版物。该提案的研究团队在模拟方面拥有丰富的集体经验， 癌症控制的比较建模，GC预防和护理领域的临床专业知识， 以及为癌症护理和政策提供信息的良好记录和承诺。拟议的三 建模组能够很好地执行并成功完成高度相关的项目目标。 拟议研究的总体目标是产生创新和范式转变 通过以医疗保健为重点的建模方法， 在美国和世界上，脆弱的高危人群承受着GC的最大负担。我们将 通过执行比较建模并完成以下目标来实现这一目标：1）开发GC 模拟模型，以估计美国人种和种族亚组的GC结果; 2)评估 风险因素趋势和初级预防策略对GC差异的影响; 3）评估目标 降低早期发病相关死亡率和GC差异的二级预防策略，以及4）调整 在全球范围内评估GC预防政策的模型。

Gastric cancer (GC), specifically gastric adenocarcinoma, is the fifth most common cancer and the third leading cause of cancer death globally and has been categorized as a neglected cancer by the World Health Organization. In the U.S., there are stark disparities, with Blacks, Hispanics and Asians having a nearly two- fold greater risk of developing or dying from GC compared to Whites, reflecting differences in risk factors, such as Helicobacter pylori (H. pylori) infection and smoking, as well as access to primary prevention and care. Several factors are changing the landscape of GC prevention, including a better understanding of the disease natural history, new evidence on prevention from prospective studies, and anticipated results from randomized controlled trials. As early GC detection can improve survival by allowing for curative surgical or noninvasive endoscopic resection, new targeted approaches to GC prevention have the potential to markedly improve population health and reduce GC disparities within the U.S. Although H. pylori has been the primary focus of global GC prevention efforts to date, substantial variation by subpopulation in H. pylori prevalence in the U.S. and the world has accentuated the need to optimize H. pylori screen-and-treat interventions for vulnerable groups. One approach is targeted endoscopic screening of high-risk individuals. For instance, persons found to have gastric intestinal metaplasia, a precursor lesion associated with a high progression risk to gastric neoplasia, are recommended to undergo endoscopic surveillance in many countries. A critical need exists to identify effective and cost-effective strategies to address these clinical challenges in the U.S., as well as globally. This proposed work builds upon prior GC work spanning GC and H. pylori simulation modeling studies, GC secondary database analyses, and relevant methodologic and global cancer modeling publications. The research team for this proposal has a vast collective experience in simulation and comparative modeling for cancer control, clinical expertise across the spectrum of GC prevention and care, and a demonstrated track record and commitment to informing cancer care and policy. The proposed three modeling groups are well-positioned to perform and successfully complete the highly relevant project aims. The overarching goal of the proposed research is to produce innovative and paradigm-shifting changes to cancer care through a disparities-focused modeling approach targeting the most vulnerable, high-risk populations that bear the greatest burden of GC in the US, and the world. We will accomplish this goal by performing comparative modeling and completing the following aims: 1) Develop GC simulation models to estimate GC outcomes for subgroups by race and ethnicity in the U.S.; 2) Assess the impact of risk factor trends and primary prevention strategies on GC disparities; 3) Evaluate targeted secondary prevention strategies for reducing early onset-related mortality and GC disparities, and 4) Adapt the models to evaluate GC prevention policies in the global setting.