Validating Cancer Risk Models: a Pilot Study to Evaluate Cost-efficient Methods

验证癌症风险模型：评估成本效益方法的试点研究

• 批准号: 8040012
• 负责人: Alice Whittemore
• 金额: $ 8.01万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-03-06 至 2012-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8040012
• 关键词: Address; Age; Australia; BRCA1 Mutation; BRCA2 gene; Breast; Breast Cancer Risk Assessment Tool; California; Canada; Cancer Model; Case-Control Studies; Cohort Studies; Costs and Benefits; Data; Disease susceptibility; Evaluation; Future; Genetic; Genotype; Goals; Gold; Guidelines; Individual; Intervention; Malignant Neoplasms; Malignant neoplasm of ovary; Methods; Modeling; Outcome; Ovary; Persons; Pike fish; Pilot Projects; Population; Prevalence; Prevention strategy; Risk; Site; Statistical Models; Study Subject; Subgroup; Testing; Variant; Weighing patient; Woman; abstracting; adverse outcome; cancer prevention; cancer risk; cancer site; case control; cohort; cost; cost effective; design; disorder prevention; genetic variant; indexing; malignant breast neoplasm; member; model development; population based; public health relevance; teacher

DESCRIPTION (provided by applicant): Validating Cancer Risk Models: a Pilot Study to Evaluate Cost-efficient Methods Abstract To facilitate targeted cancer prevention strategies and help patients weigh the costs and benefits of genetically tailored interventions, we need statistical models that provide accurate and precise projections of a person's risk of developing a given adverse outcome. Such models must be evaluated using cohort data on individuals at risk of the outcome. The ideal evaluation would genotype all subjects in a large cohort, use the genotypes to assign risks to all cohort members, and then relate assigned risks to subsequent outcomes. However such complete genotyping is too costly to be feasible. Our goal here is to test two new cost-effective methods for evaluating the added value of genetic covariates. The first is a case-cohort design that genotypes only a subset of the cohort members. The second uses case-control data and Bayes Rule to estimate the amount of increased precision gained with genotyping. Our goal is to use cohort data from the California Teachers Study (CTS) and population-based case-control data to test the two methods. We will do so by evaluating existing risk models for cancers of the ovary and breast using data from: a) all CTS subjects; b) a subset of CTS subjects in a case- cohort design; and c) subjects from a case-control study. We will use BRCAPRO scores as surrogates for pathogenic mutations of BRCA1 and BRCA2. This will allow us to compare inferences using (b) and (c) with those from (a), which will form the gold standard. PUBLIC HEALTH RELEVANCE: Project Narrative To facilitate targeted cancer prevention strategies and help patients weigh the costs and benefits of genetically tailored interventions, we need statistical models that provide accurate and precise projections of a person's risk of developing a given adverse outcome. The goal of this project is to test two new cost-effective methods for evaluating the value of adding genetic covariates to these models using data from studies of cancers of the breast and ovary.

描述（由申请人提供）：验证癌症风险模型：评估成本效益方法的试点研究摘要为了促进有针对性的癌症预防策略，并帮助患者权衡遗传定制干预措施的成本和效益，我们需要统计模型，提供准确和精确的预测一个人的风险，发展一个给定的不良后果。这些模型必须使用关于有结局风险的个人的队列数据进行评估。理想的评估是对一个大型队列中的所有受试者进行基因分型，使用基因型为所有队列成员分配风险，然后将分配的风险与随后的结果联系起来。然而，这种完全的基因分型太昂贵而不可行。我们的目标是测试两种新的成本效益的方法来评估遗传协变量的附加值。第一种是病例队列设计，仅对队列成员的子集进行基因型分析。第二种方法使用病例对照数据和贝叶斯规则来估计基因分型所增加的精确度。我们的目标是使用来自加州教师研究（CTS）的队列数据和基于人群的病例对照数据来测试这两种方法。我们将通过使用以下数据评估卵巢癌和乳腺癌的现有风险模型来实现这一点：a）所有CTS受试者; B）病例队列设计中的CTS受试者子集;以及c）来自病例对照研究的受试者。我们将使用BRCAPRO评分作为BRCA 1和BRCA 2致病性突变的替代物。这将使我们能够比较使用（B）和（c）的推论与来自（a）的推论，后者将形成黄金标准。 公共卫生关系：为了促进有针对性的癌症预防策略，并帮助患者权衡基因定制干预措施的成本和收益，我们需要统计模型，以提供对一个人发生特定不良后果的风险的准确和精确的预测。该项目的目标是测试两种新的具有成本效益的方法，用于评估使用乳腺癌和卵巢癌研究数据向这些模型添加遗传协变量的价值。