Modeling ovarian cancer screening for CEA

CEA 卵巢癌筛查建模

• 批准号: 6765872
• 负责人: Nicole Denise Urban
• 金额: $ 28.76万
• 依托单位: FRED HUTCHINSON CANCER RESEARCH CENTER
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-01 至 2006-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6765872
• 关键词: breast neoplasms; cancer risk; clinical research; cost effectiveness; early diagnosis; genetic markers; genetic screening; health care policy; health insurance; human data; mathematical model; model design /development; neoplasm /cancer epidemiology; neoplasm /cancer genetics; ovary neoplasms; prostate neoplasms; quality of life; serum; statistics /biometry

DESCRIPTION (provided by applicant): Interest in screening for ovarian cancer is growing. Five-year survival in women diagnosed with ovarian cancer is 50% overall, but in women with cancer confined to the ovaries, it is 95%. Only 25% of ovarian cancer is diagnosed in this early stage, however, suggesting that there is an opportunity for significant improvement through early detection. Our goal is to improve the accuracy of a previously developed microsimulation model of ovarian cancer screening by accounting for heterogeneity in the disease and in the population screened, in order to evaluate the cost-effectiveness of using a marker panel longitudinally to detect developing disease. We will expand the scope of the model to accommodate use of 1) a panel of serum markers for screening, and 2) risk-based screening. We will also incorporate QOL effects of both screening and disease, and update the model with respect to screening and treatment costs. These efforts will enable us to identify the potentially most efficient strategies for ovarian cancer screening and to report their cost-effectiveness. The specific aims of this study are twofold: one, to develop a state-of-the-art microsimulation model of ovarian cancer screening and two, to use the model to explore the cost-effectiveness of alternative strategies for ovarian cancer screening. There are two components to aim 2: to identify potentially cost-effective strategies for ovarian cancer screening using a panel of serum markers and imaging and to estimate the cost-effectiveness of the strategies in various populations defined by risk level. Two randomized controlled trials (RCT) of ovarian cancer screening are underway, one in the U.S. and one in the U.K., but results will not be available for several more years. Regardless of the outcomes of the RCTs, questions about cost-effectiveness, the efficacy of more frequent screening, and innovative use of multiple markers and imaging will remain. Molecular discoveries are likely soon to yield a panel of markers that can be used together as a first-line screen in a multimodal strategy involving imaging. Because it would be prohibitively expensive to conduct new RCT to test each potentially better screening strategy, an accurate simulation model will be necessary to develop sensible health care policy as well as to direct future research at both the basic and applied level. To improve the accuracy of the model's predictions, we will refine it to account for heterogeneity in the disease (histology, grade) and heterogeneity in the population screened (risk level). In addition, we will refine the detection component of the model to better represent imaging, and update the cost estimates used in the model, using insurance claims data from Regence Blue Cross of Washington State and Medicare. Extensive validation will be undertaken to assess the consistency of the model's predictions with estimates obtained from trials. Ultimately, an enhanced microsimulation model that incorporates new developments, innovations of the future as well as those we recognize today, will help guide policy and research investment decisions.

描述（由申请人提供）：筛查卵巢癌的兴趣正在增长。被诊断出患有卵巢癌的女性的五年生存率总体上为50％，但在属于卵巢的癌症的女性中为95％。然而，在这个早期阶段，只有25％的卵巢癌被诊断出来，这表明有机会通过早期检测有重大改善。我们的目标是提高先前开发的卵巢癌筛查微仿真模型的准确性，通过考虑疾病的异质性和筛查的人群的异质性，以评估纵向使用标记面板以检测发展疾病的成本效益。我们将扩大模型的范围，以适应1）血清标记面板进行筛选，以及2）基于风险的筛选。我们还将纳入筛查和疾病的质量效应，并在筛查和治疗成本方面更新模型。这些努力将使我们能够确定卵巢癌筛查的可能最有效的策略，并报告其成本效益。 这项研究的具体目的是双重的：一个是开发卵巢癌筛查的最先进的微观仿真模型，并使用该模型来探索卵巢癌筛查的替代策略的成本效益。目标2有两个组成部分：要使用一系列血清标记和成像来确定卵巢癌筛查的潜在具有成本效益的策略，并估算由风险水平定义的各种人群中这些策略的成本效益。 正在进行两项卵巢癌筛查的随机对照试验（RCT），其中一项在美国，一项在英国，但结果将在几年内再也无法获得。不管RCT的结果如何，有关成本效益，更频繁筛选的疗效以及对多个标记和成像的创新使用的问题将仍然存在。分子发现很快很快就会产生一组标记，这些标记可以在涉及成像的多模式策略中一起用作一线屏幕。由于进行新的RCT来测试每个潜在的更好的筛选策略将非常昂贵，因此对于制定合理的医疗保健政策以及指导基本和应用水平的未来研究将是必要的，必须进行准确的仿真模型。 为了提高模型预测的准确性，我们将对其进行完善以说明疾病（组织学，等级）的异质性（组织学，等级）和筛查的种群（风险水平）的异质性。此外，我们将使用来自华盛顿州和医疗保险的Regence Blue Cross的保险索赔数据来更好地表示模型的检测部分，以更好地表示模型中使用的成像。将进行广泛的验证，以评估模型预测的一致性，并通过试验获得的估计。 最终，增强的微观仿真模型纳入了新的发展，未来的创新以及我们今天认识的新发展，将有助于指导政策和研究投资决策。