STATISTICAL INNOVATIONS IN RISK MODELING

风险建模的统计创新

• 批准号: 7630030
• 负责人: Bernard A Rosner
• 金额: $ 15.21万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7630030
• 关键词: Address; Breast; Breast Cancer Epidemiology; Breast Cancer Risk Factor; Cancer Etiology; Cardiovascular system; Clear Cell; Collaborations; Colon; Colon Carcinoma; Data; Data Analyses; Development; Diet; Dietary intake; Ductal; End Point; Environment; Epidemiologic Methods; Folate; Future; Genus Cola; Goals; Haplotypes; Incidence; Individual; Intake; Investigation; Logistic Regressions; Malignant Neoplasms; Malignant neoplasm of ovary; Measurement; Measures; Methods; Modeling; Mucinous; Nutrient; Nutritional; Outcome; Range; Relative Risks; Research Personnel; Risk; Risk Factors; SAS; Screening procedure; Serous; Source; Statistical Models; Structure; Work; alcohol exposure; base; cancer risk; cohort; expectation; gene environment interaction; innovation; insight; malignant breast neoplasm; mortality; novel; prevent; validation studies

An overarching goal of this Project is to further understanding of breast, colon, and ovarian cancers, by developing and applying new methods for data analysis. Specifically, drawing on data from the cohort and from a new diet validation study to be conducted in 2006, we will address aims related to measurement error correction with repeated diet assessment. A second aim relates to the examination of combined endpoints. We will refine methods to apply polychotomous logistic regression to outcomes in Projects 1 to 3, we will apply methods to specific topics including: a. Risk factors for ductal vs. Iobular breast cancer b. Dietary exposures (alcohol, folate, etc.) vs. ER/PR status in breast cancer c. Risk factors for ovarian cancers (i). Serous vs Mucinous vs. endometrioid / clear cell ovarian cancers (ii). Mucinous vs. non-mucinous ovarian cancers Risk factors for total mortality, including cardiovascular, cancer, and other endpoints, as well as leading cancer endpoints individually, will also be examined. Statistical models, which assume constancy of relative risks for a given risk factor, may be inappropriate when a combined outcome is being evaluated, though such models are often used. Using the methods of log-incidence modeling previously applied to breast and ovarian cancer, we will draw on data from Project 2 to develop a model for colon cancer. We will also evaluate causal inference in the context of breast cancer risk factors, and haplotype estimation and geneenvironment interactions. The close collaborations among investigators in this project with those in projects 1, 2, and 3, has led to the development and application of methods and important insights into cancer etiology. Continued collaborations with investigators addressing specific cancers will provide synergy in future investigations. The close work among the investigators from various projects maximizes efficiency, provides important input from a variety of sources, prevents duplication of effort, and results in a more coherent presentation of results across endpoints.

该项目的一个主要目标是通过以下方式进一步了解乳腺癌、结肠癌和卵巢癌 开发和应用新的数据分析方法。具体地说，利用队列中的数据和 从2006年将进行的一项新的饮食验证研究中，我们将解决与测量相关的目标 通过重复的饮食评估进行纠错。第二个目标是审查合并后的 终端。我们将改进将多分类Logistic回归应用于项目1至项目结果的方法 3、我们将针对具体主题应用方法，包括： A.导管与小叶乳腺癌的危险因素 B.饮食暴露(酒精、叶酸等)乳腺癌与雌激素受体/孕激素受体状态的关系 C.卵巢癌的危险因素 (I)。浆液性卵巢癌与粘液性卵巢癌与子宫内膜样癌/透明细胞癌 (Ii)。粘液性卵巢癌与非粘液性卵巢癌 总死亡率的风险因素，包括心血管疾病、癌症和其他终点，以及主要 癌症终点，也将进行检查。假设相对不变的统计模型 然而，当评估综合结果时，给定风险因素的风险可能是不合适的 这样的模型经常被使用。使用先前应用于乳房和乳房的对数-关联建模方法 对于卵巢癌，我们将利用项目2的数据来开发结肠癌的模型。我们还将 在乳腺癌危险因素、单倍型估计和遗传环境的背景下评估因果推断 互动。 这个项目中的调查人员与项目1、2和3中的调查人员密切合作， 导致了癌症病因学方法和重要见解的发展和应用。续 与针对特定癌症的研究人员的合作将在未来的研究中提供协同效应。 来自各个项目的调查人员之间的密切合作最大限度地提高了效率，提供了重要的 来自各种来源的输入，防止重复工作，并导致更连贯的陈述 跨终端的结果。