Collaborative Research: Mathematical Modeling of Dynamic Breast Cancer Screening

合作研究：动态乳腺癌筛查的数学模型

• 批准号: 0423090
• 负责人: Julie Ivy
• 金额: $ 6.12万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0423090&HistoricalAwards=false
• 关键词: Collaborative; Research; Mathematical; Modeling; Dynamic

This grant provides funding for the development of a mathematical model to examine whether different mammogram screening intervals should be used pre-menopause and post-menopause. Analysis of this model will provide insight into the following questions: how worthwhile is it, in terms of mortality risk, to use different mammogram intervals in the pre- and post-menopausal phases? Should screening be more frequent pre- or post-menopause? How does screening start-age/stop-age affect mortality risk? These questions are particularly interesting given the dynamic nature of breast cancer incidence, breast cancer aggression, and mammogram-efficacy between the pre- and post-menopausal phases. Using a partially observed Markov decision process model, different screening policies will be evaluated, and informative tradeoff curves that plot some measure of "policy effort" versus mortality risk will be constructed. Attention will be restricted to two types of policies: "routine" policies that prescribe the same screening interval over the life of the patient, and "two-phase" policies that prescribe one interval pre-menopause and a different interval post-menopause. The results of this research will potentially benefit society through patient-empowerment and improved public policy. The tradeoff curves will allow women to tailor their own mammogram screening choices based on individual risk preference, economic status, insurance coverage, incidence propensity, etc.. The tradeoff curves will present the quantitative relationship between screening policy and mortality risk in a format that is both understandable and useful for "non-scientists." If successful, the outcomes of the proposed research may also impact American Cancer Society policy recommendations for breast cancer screening.

该赠款为开发数学模型提供了资金，以检查是否应使用少年前和培训后使用不同的乳房X线照片筛查间隔。对该模型的分析将提供有关以下问题的见解：在死亡率风险方面，在绝经前和绝经后阶段使用不同的乳房X线照片间隔有多价值？筛查是否应该更频繁地培训前后？ 筛查开始时代/停止年龄如何影响死亡率风险？鉴于乳腺癌发生率，乳腺癌攻击性以及绝经后和绝经后阶段之间的乳腺癌效率的动态性质，这些问题尤其有趣。使用部分观察到的马尔可夫决策过程模型，将评估不同的筛选政策，并将构建一定程度的权衡曲线，以构建某种措施“政策努力”与死亡风险的措施。 注意将仅限于两种类型的政策：“常规”政策，这些政策在患者的生活中开出相同的筛查间隔，以及“两阶段”政策，这些政策规定了一个间隔前的概述前的间隔和另一间间隔后期的途中。 这项研究的结果将通过赋权和改善公共政策来使社会受益。 权衡曲线将允许妇女根据个人风险偏好，经济状况，保险，发病率倾向等量身定制自己的乳房X线照片筛查选择。折衷曲线将以既可以理解又对“非科学家”既可以理解又有用的格式之间的定量关系呈现定量关系。 如果成功，拟议研究的结果也可能影响美国癌症协会的乳腺癌筛查政策建议。