Cancer Clustering for Residential Histories

居住史的癌症聚类

• 批准号: 7474728
• 负责人: Geoffrey M. Jacquez
• 金额: $ 37.5万
• 依托单位: BIOMEDWARE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7474728
• 关键词: Accounting; Achievement; Address; Algorithms; Area; Arts; Atlas of Cancer Mortality in the United States; Behavior; Bladder; Breast; Businesses; California; Cancer Burden; Cancer Cluster; Cancer Control; Cancer Etiology; Carcinogens; Case Study; Case-Control Studies; Cessation of life; Cluster Analysis; Code; Complex; Computer Simulation; Computer software; County; Data; Data Analyses; Data Set; Depth; Detection; Development; Diagnosis; Disease; Economics; Educational process of instructing; Educational workshop; End Point; Environmental Exposure; Environmental Risk Factor; Epidemiology; Evaluation; Event; Failure; Foundations; Generations; Geographic Information Systems; Geographic Locations; Geography; Goals; Health; Household; Human; Imagery; Incidence; Individual; Industry; Information Systems; Intelligence; Intervention; Investigation; Knowledge; Lead; Legal patent; Life; Life Cycle Stages; Link; Literature; Localized; Location; Logistic Models; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Maps; Marketing; Medical Surveillance; Methodology; Methods; Metric; Michigan; Modeling; Monitor; Morbidity - disease rate; Outcome; Paper; Participant; Pattern; Peer Review; Phase; Phase I Clinical Trials; Plague; Population; Population Study; Principal Investigator; Probability; Procedures; Protocols documentation; Public Health Students; Publications; Randomized; Range; Recording of previous events; Relative (related person); Reliability of Results; Research; Research Personnel; Residential Mobility; Risk; Risk Factors; Science; Software Tools; Source; Space-Time Clustering; Statistically Significant; System; Teaching Materials; Techniques; Technology; Testing; Time; To specify; Uncertainty; United States; United States National Institutes of Health; Universities; Use of New Techniques; Variant; Water Supply; abstracting; analytical tool; animation; base; cancer diagnosis; cancer risk; carcinogenesis; case control; commercial application; commercialization; data modeling; data structure; design; geographic difference; hazard; improved; innovation; malignant breast neoplasm; member; mortality; neoplasm registry; novel strategies; programs; prototype; rapid growth; residence; simulation; social; software development; software systems; statistics; symposium; tool; trend

DESCRIPTION (provided by applicant): Cancer Clustering for Residential Histories Abstract: This project will develop a new, comprehensive approach for evaluating clustering in case-control data that accounts for residential histories, risk factors, covariates and cancer induction and latency periods. To date, two of the major deficiencies of geographic studies of cancer are that they lack an appropriate methodology for investigating clusters over the life course and risk factors/covariates are not included in the analysis. These limitations are overcome by this project. Local, global and focused tests for residential histories will be developed based on sets of matrices of nearest neighbor relationships that reflect the changing space-time geometry of the residential addresses of cases and controls. Exposure traces that account for the latency between exposure and disease manifestation, and that use exposure windows of varying duration will be defined. Several of the methods so derived will be applied to evaluate clustering of residential histories in an ongoing case-control study of bladder cancer in south eastern Michigan, and to identify local excesses of breast cancer in Marin County, California. Because humans are mobile, these new methods are a significant advance over approaches that ignore residential histories and instead rely only on place of residence at time of diagnosis or death. The major innovation is the creation of methods for analyzing and modeling the residential histories of cases and controls to identify geographic excesses of cancer risk, both in the study population itself as well as in relation to putative hazards such as point-source releases of carcinogens. Cancer Clustering for Residential Histories Relevance: The techniques and software to be developed in this project will provide a more concise and accurate description of clustering of cancer cases that accounts for risk factors, covariates, residential history, cancer latency, time of diagnosis, and the exposure windows during which causative exposures are hypothesized to have occurred. To our knowledge the techniques and software from this project will be the first to address all of these factors within a single, comprehensive framework.

描述（申请人提供）：住宅历史的癌症聚类摘要：该项目将开发一种新的，全面的方法，用于评估案例对照数据中的聚类，该数据对住宅历史，风险因素，协变量，癌症诱导和潜伏期期。迄今为止，癌症地理研究的两个主要缺陷是，它们缺乏适当的方法来研究生命过程中的集群，而危险因素/协变量不包括在分析中。该项目克服了这些限制。将根据最近的邻居关系的矩阵集合开发针对住宅历史的本地，全球和集中测试，这些矩阵反映了案件和控制措施的住宅地址的不断变化的时空几何形状。曝光痕迹将定义暴露与疾病表现之间的潜伏期，以及使用不同持续时间的使用窗户的潜伏期。在正在进行的密歇根州东南部膀胱癌的病例对照研究中，将采用的几种方法将用于评估住宅历史的聚类，并确定加利福尼亚州马林县的局部过度乳腺癌。由于人类是流动的，因此这些新方法是忽略居民历史的方法，而不是在诊断或死亡时仅依靠居住地。主要的创新是创建用于分析和建模病例和对照的住宅历史的方法，以识别研究人群本身以及与假定危害（例如癌症释放）的癌症风险的地理过剩。针对住宅历史相关的癌症聚类：该项目中要开发的技术和软件将对癌症病例的聚类进行更简洁，准确的描述，这些癌症病例的聚类涉及风险因素，协变量，住宅病史，癌症潜伏期，诊断时间和癌症病例。暴露窗口假设发生致病暴露是发生的。据我们所知，该项目的技术和软件将是第一个在一个全面的框架内解决所有这些因素的技术。