The Effect of Aflatoxin Regulation on Global Liver Cancer Risks

描述（由申请人提供）：尤里卡申请的目的是开发一种多因素建模工具，可为决策者提供有关如何制定降低全球肝癌发病率的食源性黄曲霉毒素标准的信息。肝癌（肝细胞癌）是全球癌症死亡的第三大原因，其发病率随着慢性B肝炎（HBV）和丙型肝炎（HCV）感染的增加而增加。黄曲霉毒素是一种有效的肝癌原，与HBV和HCV协同作用，产生比单独暴露高30倍的肝癌风险。黄曲霉毒素是由真菌黄曲霉和A.在温暖的气候条件下，玉米和花生中的寄生虫。因此，全球人群中黄曲霉毒素诱导的肝癌风险最大的是那些消费高水平玉米和花生的人，在热带和亚热带的欠发达国家（LDCs），控制黄曲霉毒素的资源稀缺。我们假设，模拟公共卫生影响和贸易/经济后果的计算模型可以为监管标准如何改善全球癌症负担提供独特的见解。100多个国家已经制定了食品中黄曲霉毒素最大允许含量的标准。这些标准因国而异。目前正在努力协调全球黄曲霉毒素标准，以防止世界食品贸易争端。我们提出的问题是：黄曲霉毒素的统一标准应该是什么，才能最好地保护全球健康？具有讽刺意味的是，制定一个非常严格的标准可能会导致更多的癌症病例，原因有三：1。由于肝炎发病率低，富裕的粮食进口国的健康益处有限，而粮食出口最不发达国家为达到这些标准可能要付出过高的代价。 2.限制粮食出口市场可能会加剧最不发达国家的贫困，从而加剧饥饿和健康状况不佳，导致肝炎感染和肝癌风险增加。 3.为了保护其出口市场，亚洲和非洲国家可能会试图出口其最优质的食品，并将污染最严重的食品留在国内，这增加了世界上目前肝炎感染率最高的地区黄曲霉毒素消费和肝癌的风险。由于进行临床试验既不实际也不道德，回顾性数据有限，计算机模拟建模是一种非常有用的技术，可以检查不同的全球黄曲霉毒素标准对食品贸易和癌症发病率的影响。公共卫生决策分析方法的一个强大属性是同时评估多个维度的能力。我们寻求创建一个创新的建模工具，将全球肝癌和肝炎发病率，玉米和坚果的黄曲霉毒素暴露，成本和技术变化整合到一个单一的决策分析框架中。我们的具体目标是确定在当前条件和未来情景下，选定的统一黄曲霉毒素标准对全球食品出口损失和黄曲霉毒素诱导的肝癌全球负担的影响。

DESCRIPTION (provided by applicant): The purpose of this EUREKA application is to develop a multi-factorial modeling tool that can provide decision- makers information on how to set foodborne aflatoxin standards that reduce global liver cancer incidence. Liver cancer (hepatocellular carcinoma) is the 3rd-leading cause of cancer deaths worldwide, with an increasing incidence that parallels the rise in chronic hepatitis B (HBV) and hepatitis C (HCV) infection. Aflatoxin is a potent hepatocarcinogen that synergizes with HBV and HCV to produce 30-fold higher liver cancer risk than either exposure alone. Aflatoxin is produced by the fungi Aspergillus flavus and A. parasiticus in maize and peanuts under warm climatic conditions. Hence, the global populations most at risk of aflatoxin-induced liver cancer are those who consume high levels of maize and peanuts, in less developed countries (LDCs) in the tropics and subtropics where resources to control aflatoxin are scarce. We hypothesize that computational modeling that simulates both public health effects and trade / economic consequences can provide unique insights into how regulatory standards can ameliorate global cancer burden. Over 100 nations have set standards on maximum allowable aflatoxin levels in food. These standards vary widely from nation to nation. Efforts are now being made to harmonize aflatoxin standards globally, to prevent world food trade disputes. We address the question: What should the harmonized aflatoxin standard be to best protect global health? Ironically, setting a very strict standard could result in more cancer cases, for 3 reasons: 1. Rich, food-importing countries would have limited health benefits because of low hepatitis prevalence, while food-exporting LDCs may incur excessive costs to meet such standards. 2. Limiting food export markets could increase poverty in LDCs, which would augment hunger and poor health conducive to increased hepatitis infection and liver cancer risk. 3. To preserve their export markets, Asian and African nations may attempt to export their best-quality food and keep the most highly contaminated food domestically, raising the risk of aflatoxin consumption and liver cancer in parts of the world that currently have the highest rates of hepatitis infection. Because conducting clinical trials is neither practical nor ethical, and retrospective data are limited, computer simulation modeling is an extremely useful technique to examine the consequences of different global aflatoxin standards on food trade and cancer incidence. A powerful attribute of the decision analytic approach to public health is the ability to evaluate several dimensions simultaneously. We seek to create an innovative modeling tool that integrates global liver cancer and hepatitis incidence, aflatoxin exposure through maize and nuts, costs, and technological changes into a single decision-analytic framework. Our specific aim is to determine the effect of selected harmonized aflatoxin standards on both global food export losses and global burden of aflatoxin-induced liver cancer, under current conditions and future scenarios.