Collaborative Research: Case-Control Studies, New Directions and Applications

合作研究：病例对照研究、新方向和应用

• 批准号: 1007494
• 负责人: Bhramar Mukherjee
• 金额: $ 11.89万
• 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: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1007494&HistoricalAwards=false
• 关键词: Collaborative; Research; Case; Control; Studies

Case-control studies mark possibly the single most important and far-reaching contribution that statisticians have made in the domain of Public Health and Epidemiology. The prime objective of this research is to make some new contributions to case-control studies, both in methodology and in application. In particular, the PIs propose a semiparametric Bayesian method to incorporate longitudinal data in a case-control analysis using penalized splines. New Bayesian functional data-analytic tools are needed here. The methods will be applied to biomarker based screening procedures, and will provide a critical appraisal of the association between prostate cancer and the past trajectory of prostate-specific antigen measurements. A second component of the proposed research is the analysis of case-control data generated from two-phase sampling with non-monotone missingness in covariates. Such designs have many potential applications in case-control studies that explore interplay of genetic and environmental risk factors. Exploiting assumptions like gene-gene and gene-environment independence adds to the complexity of the inference. The methods are motivated by an immediate application to a large population based case-control study of colorectal cancer. The final aspect of this proposal deals with a united methodology which provides equivalent inference for odds ratio parameters based on prospective and retrospective models. Both frequentist and Bayesian methods will be considered. The PIs have a track record of successful collaboration in this domain, and want to advance/ extend their work further in these new directions. Two scientific streams are currently dominating clinical medicine and public health: the molecular biology approach with an emphasis on genetics and discovery of novel biomarkers, and the quantitative approach with an emphasis on epidemiology. The developments in these areas jointly are making fundamental contributions to the study of etiology, diagnosis, prognosis and treatment of complex diseases. Though the standard unmatched case-control study design still remains one of the most popular epidemiologic tools, phenomenal advancement of medical science and genetic technology is giving rise to many complex design and analysis issues which statisticians and epidemiologists have never confronted before. This proposal lies in that new interface of epidemiology and statistics. To understand the mechanism of complex diseases and to design targeted intervention strategies for high-risk individuals is one of the major areas of scientific research in this century. The current proposal is not a mere academic pursuit but an effort to contribute to this scientific process.

病例对照研究可能是统计学家在公共卫生和流行病学领域做出的最重要、影响最深远的贡献。本研究的主要目的是在方法学和应用方面对病例对照研究作出一些新的贡献。特别是，pi提出了一种半参数贝叶斯方法，将纵向数据纳入使用惩罚样条的病例对照分析中。这里需要新的贝叶斯函数数据分析工具。这些方法将应用于基于生物标志物的筛选程序，并将提供前列腺癌与前列腺特异性抗原测量的过去轨迹之间关系的关键评估。所提出的研究的第二个组成部分是分析由协变量非单调缺失的两阶段抽样产生的病例对照数据。这种设计在探索遗传和环境风险因素相互作用的病例对照研究中有许多潜在的应用。利用诸如基因-基因和基因-环境独立的假设增加了推理的复杂性。这些方法的动机是立即应用于基于大量人群的结直肠癌病例对照研究。本建议的最后一个方面涉及一个统一的方法，该方法提供了基于前瞻性和回顾性模型的比值比参数的等效推断。频率方法和贝叶斯方法都将被考虑。pi在这个领域有成功合作的记录，并希望在这些新方向上进一步推进/扩展他们的工作。目前临床医学和公共卫生主要有两种科学流派：强调遗传学和发现新的生物标志物的分子生物学方法，以及强调流行病学的定量方法。这些领域的发展共同为复杂疾病的病因、诊断、预后和治疗的研究做出了根本性的贡献。尽管标准的无与伦比的病例对照研究设计仍然是最流行的流行病学工具之一，但医学科学和基因技术的惊人进步正在产生许多统计学家和流行病学家从未遇到过的复杂设计和分析问题。这个建议在于流行病学和统计学的新接口。了解复杂疾病的发病机制，针对高危人群设计有针对性的干预策略，是本世纪科学研究的主要领域之一。目前的建议不仅仅是学术上的追求，而是努力为这一科学进程做出贡献。