A POPULATION-BASED POLICY MODEL FOR COLORECTAL CANCER

该项目的目的是进一步发展一种基于人口的政策模式，专门用于美国结直肠癌的预防、检测和治疗。 该模型将是对美国人口的动态蒙特卡罗模拟，其中包括流行病学研究中发现的与结直肠癌发病率相关的所有可修改和不可修改的风险因素：吸烟史、体重指数、体力活动、红肉消费、水果和蔬菜消费、阿司匹林使用、多种维生素使用（作为叶酸摄入量的代表）、饮酒、绝经后激素使用、结直肠癌家族史以及人口统计学变量（年龄、性别、种族）。 风险方程将主要来自护士健康研究和卫生专业人员随访研究;美国人群中风险因素随时间的分布将主要来自NHANES I、II和III。 该模型将跟踪腺瘤性息肉和未诊断癌症的潜在进展和位置，从而使筛查测试能够检测和去除腺瘤性息肉，或可能在早期检测癌症。 一旦癌症被检测和分期（通过筛查测试或症状），所有相关的结直肠癌治疗策略将被纳入，从而可以评估当前或假设的干预措施。 该模型将用于分析观察到的癌症趋势的潜在贡献者，并预测对风险因素干预，筛查和结直肠癌治疗的国家趋势的潜在影响。在整个项目中，研究小组将与国家癌症研究所合作，整合国家数据源并集中研究问题。 研究小组还将与其他建模小组一起进行校准，验证和模型结果的比较。

The purpose of this project is to further develop a population- based policy model that is specific for the prevention, detection, and treatment of colorectal cancer in the United States. The model will be a dynamic Monte Carlo simulation of the U.S. population that will include all of the modifiable and non-modifiable risk factors that have been found in epidemiological studies to be associated with the incidence of colorectal cancer: smoking history, body mass index, physical activity, red meat consumption, fruit and vegetable consumption, aspirin use, multivitamin use (as a proxy for folate intake), alcohol consumption, postmenopausal hormone use, and family history of colorectal cancer, as well as demographic variables (age, gender, race). Risk equations will be derived primarily from the Nurses' Health Study and the Health Professionals Follow-up Study; risk factor distributions over time in the U.S. population will be obtained primarily from the NHANES I, II, and III. The model will track the underlying progression and location of adenomatous polyps and undiagnosed cancer, thus enabling a screening test to detect and remove an adenomatous polyp, or to possibly detect a cancer at an earlier stage. Once a cancer is detected and staged (either by a screening test or by symptoms), all relevant colorectal cancer treatment strategies will be incorporated, allowing for the evaluation of current or hypothetical interventions. The model will be used to analyze the potential contributors to the observed cancer trends and to predict the potential impact on national trends of risk factor interventions, screening, and colorectal cancer treatment. Throughout this project, the research team will collaborate with the National Cancer Institute to incorporate national data sources and to focus research questions. The research team will also be involved with other modeling groups for purposes of calibration, validation, and the comparison of model results.