Measurement Errors in Cancer Epidemiology

癌症流行病学中的测量误差

• 批准号: 7294327
• 负责人: DONNA L SPIEGELMAN
• 金额: $ 46.97万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-07-17 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7294327
• 关键词: Address; Arsenic; Biological Markers; Breast; Cancer Etiology; Cohort Studies; Colon; Cox Models; DNA Microarray Chip; DNA Microarray format; Data; Diet; Disease; Disease regression; Echocardiography; Energy Intake; Environment; Environmental Exposure; Follow-Up Studies; Food; Frequencies; Gene Expression; Genetic; Genomics; Genotype; Genus Cola; Goals; Grant; Haplotypes; Health Professional; Incidence; Intake; Investigation; Label; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Measures; Methods; Modeling; New Hampshire; Nitrogen; Nurses' Health Study; Nutrient; Nutritional; Nutritional Study; Outcome; Persons; Prevention; Probability; Process; Proteins; Questionnaires; Range; Rate; Relative (related person); Reporting; Research; Research Design; Risk; Risk Estimate; Risk Factors; Role; SNP genotyping; Score; Statistical Methods; Surveys; Techniques; Time; Triad Acrylic Resin; Ultrasonography; Validation; Variant; Water; Weight; Work; base; cancer epidemiology; case control; design; diet and cancer; improved; instrument; interest; method development; mortality; musculoskeletal ultrasound; prospective; response; software development; trend; urinary; user-friendly; validation studies

DESCRIPTION (provided by applicant): Exposure measurement errors in cancer epidemiology pose special methodologic challenges. For example, nutritional exposures form the basis for many etiologic hypotheses concerning cancer. However, nutrient intake is difficult to measure precisely. Other important examples considered in this grant include genomic risk factors and environmental exposures. It is the role of measurement error correction methods to estimate the relationship between cancer outcomes and exposures. To accomplish this requires both a main study where disease and the surrogate exposure are measured and validation data to determine the extent of the measurement error. In this proposal, we seek to continue our group's previous work on methods of corrections for measurement error and misclassification. A major focus is on nutritional studies based on intakes reported at a single survey when the target exposure is long-term average diet. Here, the dependent variable is time to cancer incidence or mortality; thus, Cox models are considered in which time-varying covariates such as cumulative averages and cumulative exposures are of primary interest. Another goal is to extend methods for random and subject-specific error terms when the usual exposure measurements and the reference exposure measurements may be correlated. These methods will be applied to a recent USDA study of assessment of energy intake using doubly labeled water and a re-analysis of the NCI's OPEN study of assessment of energy intake. Instrumental variables methods for nonlinear environmental exposure response estimation developed in the previous grant period will be extended to address gene expression response from DNA microarray data assessed longitudinally. These methods are to be applied to data from the New Hampshire Arsenic and Cancer Study. Finally, methods are proposed for genetic and genomic data increasingly being used in cancer epidemiology. Here, we propose to assess the extent to which bias in relative risk estimates is induced by SNP and haplotype misclassification, and develop new corrected estimators. User-friendly, public use software development will be a focus of all new methods development.

描述（由申请人提供）：癌症流行病学中的暴露测量错误构成了特殊的方法论挑战。例如，营养暴露构成了许多有关癌症的病因学假设的基础。但是，营养摄入量很难精确测量。该赠款中考虑的其他重要例子包括基因组风险因素和环境暴露。它是测量误差校正方法的作用，可以估计癌症结局与暴露之间的关系。为了实现这一目标，既需要一项疾病和替代暴露的主要研究，又需要验证数据，以确定测量误差的程度。在此提案中，我们试图继续我们小组以前关于测量错误和错误分类方法的矫正方法的工作。主要重点是基于在目标暴露是长期平均饮食时在一次调查中报道的摄入量的营养研究。在这里，因变量是癌症发病率或死亡率的时间。因此，考虑到COX模型，随着时间变化的协变量（例如累积平均值和累积暴露）是主要利益的。另一个目标是在通常的暴露测量值和参考暴露测量值时，扩展了随机和主题特定误差项的方法。这些方法将应用于最近对使用双重标记的水评估能量摄入评估以及对NCI对能量摄入评估的开放研究的重新分析的研究。在上一个赠款期间开发的非线性环境暴露响应估计的仪器变量方法将扩展，以解决纵向评估的DNA微阵列数据的基因表达响应。这些方法应应用于新罕布什尔州砷和癌症研究的数据。最后，提出了越来越多地用于癌症流行病学中的遗传和基因组数据的方法。在这里，我们建议评估SNP和单倍型错误分类引起相对风险估计中的偏差的程度，并开发新的校正估计器。用户友好的公共使用软件开发将成为所有新方法开发的重点。