Models for cumulative spatial-temporal assessment of non-Hodgkin lymphoma risk

非霍奇金淋巴瘤风险累积时空评估模型

• 批准号: 8703044
• 负责人: David Charles Wheeler
• 金额: $ 7.4万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-17 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8703044
• 关键词: Accounting; Address; Applications Grants; Area; Case-Control Studies; Complex; Data; Development; Diagnosis; Dimensions; Disease; Disease model; Enrollment; Environment; Environmental Exposure; Environmental Risk Factor; Epidemiologic Studies; Epidemiology; Etiology; Evaluation; Exposure to; Foundations; Genetic; Geographic Locations; Home environment; Incidence; Individual; Iowa; Lead; Life; Life Cycle Stages; Location; Los Angeles; Malignant Neoplasms; Methodology; Methods; Modeling; National Cancer Institute; Non-Hodgkin' s Lymphoma; Outcomes Research; Pattern; Performance; Population; Public Health; Publishing; Recording of previous events; Research; Residential Mobility; Risk; Risk Assessment; Risk Factors; Statistical Methods; Statistical Models; Study Subject; Time; Uncertainty; United States; Work; base; cancer diagnosis; cancer risk; disorder risk; epidemiology study; genetic risk factor; insight; lifestyle factors; mortality; novel; novel strategies; pollutant; population based; public health relevance; residence; simulation; time use

DESCRIPTION (provided by applicant): Many cancers have established or suspected risk factors that are distributed unevenly in the environment. Exploring spatial patterns of cancer incidence and mortality can identify areas of significantly elevated risk and provide potential etiologic clues. Increasingly, residential addresses at time of diagnosis or study enrollment and even complete residential histories are collected in epidemiologic studies of cancer that enable a finer level of spatial analysis than in ecological studies. In spatial epidemiology studies of cancer risk the residential location is often used as a surrogate for the unknown environmental exposures that occur in and around the home. However, several methodological challenges arise in spatial analysis of cancer in epidemiologic studies when considering the temporal dimension of risk. Cumulative environmental exposures are not assessed and disease latency and population mobility are ignored when using the residential location at time of diagnosis as a marker for environmental exposures. There is a need for development and assessment of statistical methods to model cumulative spatial-temporal cancer risk in epidemiologic studies with residential histories while accounting for population mobility, disease latency, and known disease risk factors. The specific aims of this research are 1) to develop cumulative spatial-temporal models of cancer risk and apply them to a case-control study of non-Hodgkin lymphoma (NHL) with residential histories, 2) to evaluate the accuracy of the statistical models for detecting areas of significant risk over time, and 3) to investigate possible exposures that may be associated with any detected areas of significantly elevated risk. NHL is suitable for a spatial pattern analysis because it is a cancer with an unclear etiology and established risk factors that account for only a small proportion of the total annual NHL cases in the United States. The expected outcomes of this research will be 1) new statistical approaches to model spatial-temporal risk that consider life-course environmental exposures, 2) a thorough assessment of the accuracy of the models, and 3) identification of areas of significant risk of NHL in space and time in four areas (Detroit, Iowa, Los Angeles, Seattle) of the United States. The significance of this research is two-fold. First, the development and evaluation of new approaches to spatial-temporal risk analysis that better consider life-course environmental exposures will advance the field of spatial analysis research. Second, this will be the first cumulative spatial-temporal risk analysis of a case-control study of NHL, which also adjusts for known environmental, genetic, and demographic risk factors. The work in this research application will serve as the foundation for a larger grant application to the National Cancer Institute to model spatial-temporal uncertainty in cancer risk. The assessment of the performance of new and existing methods for modeling spatial risk of cancer over time will be used to guide the selection and refinement of methods for inclusion in the later application and to demonstrate the benefits of the proposed approach to other cancers.

描述（由申请人提供）：许多癌症已经建立了或怀疑在环境中分布不均的风险因素。探索癌症发病率和死亡率的空间模式可以识别风险显着升高的领域，并提供潜在的病因线索。在诊断或研究入学时，越来越多的住宅地址在癌症的流行病学研究中收集了比生态学研究更优质的空间分析。在癌症风险的空间流行病学研究中，住宅位置通常用作房屋内及其周围未知环境暴露的替代物。但是，在考虑风险的时间维度时，在流行病学研究中对癌症的空间分析中出现了一些方法上的挑战。未评估累积环境暴露，疾病潜伏期和诊断时使用住宅位置作为环境暴露的标志时，人口流动性被忽略。需要开发和评估统计方法，以模拟具有住宅历史的流行病学研究中累积的空间癌风险，同时考虑了人口流动性，疾病潜伏期和已知疾病危险因素。这项研究的具体目的是1）开发癌症风险的累积时空模型，并将其应用于具有住宅历史的非霍奇金淋巴瘤（NHL）（NHL）的病例对照研究，2）评估统计模型的准确性，以检测与可能相关的风险相关的大量风险，并可能与任何相关的风险相关。 NHL适用于空间模式分析，因为它是一种具有不清楚的癌症，并且确定了风险因素，仅占美国NHL年总病例的一小部分。这项研究的预期结果将是1）建模考虑生命过程环境暴露的时空风险的新统计方法，2）对模型的准确性进行彻底评估，3）识别NHL在四个地区（底特律，爱荷华州，洛斯，洛斯，西特，西特，美国）的空间和时间上有明显的空间和时间风险的区域。这项研究的意义是两倍。首先，更好地考虑生命过程环境暴露的新方法的开发和评估将推进空间分析研究领域。其次，这将是NHL病例对照研究的首次累积时空风险分析，该研究还可以调整已知的环境，遗传和人口统计风险因素。本研究申请中的工作将为国家癌症研究所提供更大的赠款申请，以模拟癌症风险中的时空不确定性。随着时间的推移，对新的和现有方法进行建模癌症的空间风险的性能的评估将用于指导选择和完善后来应用中包含的方法，并证明对其他癌症提出的方法的好处。