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：一项试点研究，以评估具有成本效益的方法摘要，以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成本和收益，我们需要统计模型，这些模型可提供准确，精确的预测者对一个人产生给定不良结果的风险的预测。必须使用有关有结果风险的个体数据来评估此类模型。理想的评估将基因类型的大型队列中的所有受试者，使用基因型为所有队列成员分配风险，然后将指定的风险与后续结果相关联。但是，这种完整的基因分型太昂贵而无法可行。我们的目标是测试两种评估遗传协变量附加值的新的成本效益方法。首先是一个病例 - 霍特设计，仅基因型仅一部分队列成员的子集。第二种使用病例对照数据和贝叶斯规则来估计通过基因分型获得的精度增加的量。我们的目标是使用来自加利福尼亚教师研究（CTS）和基于人群的病例对照数据的队列数据来测试这两种方法。我们将使用以下数据来评估卵巢和乳腺癌的现有风险模型：a）所有CTS受试者； b）案例组设计中的CTS受试者的子集； c）来自病例对照研究的受试者。我们将使用BRCAPRO评分作为BRCA1和BRCA2致病突变的替代物。这将使我们能够使用（b）和（c）与（a）的推论进行比较，这将构成黄金标准。 公共卫生相关性：项目叙述，以促进有针对性的癌症预防策略，并帮助患者权衡基因量身定制干预措施的成本和收益，我们需要统计模型，这些模型可提供准确，精确的预测，以了解一个人有发展给定不利结果的风险。该项目的目的是测试两种新的具有成本效益的方法，以使用乳腺癌和卵巢癌研究的数据来评估将遗传协变量添加到这些模型中的价值。