Disparities in Cancer Prevention and Control

描述（由申请人提供）：该项目的目的是扩展我们目前在癌症决策分析政策模型开发方面的工作，以量化筛查，随访和治疗差异对癌症相关结果的影响。我们将首先开发一个可推广的模型，作为一个框架，将差异纳入决策分析模型。我们将关注癌症风险，癌症筛查参与率，治疗模式及其相互作用的差异。我们将评估几种假设情况，以突出最令人关注的差异领域。此外，我们将利用我们已经完成的工作，开发特定群体的模拟模型，以解决对某些人群产生不成比例影响的社会相关政策问题。 我们会就三种主要癌症的问题进行分析：结直肠癌、宫颈癌和乳腺癌。 这些模型将作为蒙特卡罗模拟（每次一个人）进行评估，在跟踪个人具体变量方面提供了很大的灵活性。结肠直肠癌和宫颈癌模型模拟从正常宫颈或正常结肠上皮到癌前病变（即，腺瘤性息肉为前者模型，宫颈病变为后者模型）转为恶性。癌症诊断发生时，筛查测试是应用于一个人与未确诊的恶性肿瘤（根据测试的敏感性），或者如果症状发生，导致正确的诊断（确诊癌症）。一旦癌症被检测和分期，可以纳入影响癌症特异性死亡率的特定治疗策略的细节。癌症特异性模型将用于分析差异的重要贡献者的影响以及它们与癌症控制的关系。

DESCRIPTION (PROVIDED BY APPLICANT): The purpose of this project is to extend our current work on the development of decision-analytic policy models in cancer to quantify the impact of disparities in screening, follow-up, and treatment in terms of its impact on cancer-related outcomes. We will initially develop a generalizable model that will serve as a framework for incorporating disparities in decision-analytic models. We will focus on disparities in cancer risk, cancer screening participation rates, treatment patterns, and their interactions. We will evaluate several hypothetical situations to highlight those areas where disparities are most concerning. In addition, we will leverage the work that we have already done to develop cohort-specific simulation models to address socially relevant policy questions that disproportionately affect certain segments of the population. We will conduct analyses for questions pertaining to three major cancers: colorectal, cervical and breast. The models will be evaluated as Monte Carlo simulations (one person at a time), which provide a substantial amount of flexibility in terms of keeping track of person-specific variables. The colorectal cancer and cervical cancer models simulate the evolution from a normal cervix or normal colonic epithelium to precancerous lesions (i.e., adenomatous polyps for the former model, cervical lesions for the latter) to malignancy. Cancer diagnosis occurs when a screening test is applied to a person with undiagnosed malignancy (based on the test sensitivity), or if symptoms occur that lead to a correct diagnosis (symptom-diagnosed cancer). Once a cancer is detected and staged, details of specific treatment strategies can be incorporated that affect cancer-specific mortality. The cancer-specific models will be used to analyze the effects of important contributors to disparities and how they relate to cancer control.