A Temporal-Spatial Analysis of Breast Cancer in Upper C*

上 C* 乳腺癌的时空分析

• 批准号: 7058552
• 负责人: Veronica M Vieira
• 金额: $ 8.08万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7058552
• 关键词: breast neoplasms; cancer risk; clinical research; environment related neoplasm /cancer; environmental exposure; female; geographic site; housing; human data; mathematical model; model design /development; neoplasm /cancer epidemiology; statistics /biometry; time resolved data; women' s health

DESCRIPTION (provided by applicant): The reason for elevated breast cancer rates on Cape Cod, Massachusetts remains unknown despite epidemiological studies to investigate possible environmental risk factors. Two existing population-based breast cancer case-control studies of upper Cape Cod (1983-1993) provide a geocoded residential history and information on confounders for all subjects. Combining the two studies creates an invaluable dataset for temporal-spatial analysis of subjects' residences from 1943 to 1993. Geographic Information Systems (GIS) have allowed the use of spatial analytic techniques in public health studies previously not feasible. Generalized Additive Models (GAMs) are an effective approach to mapping spatial distributions of data, combining a number of desirable features: smoothing of geographical location and calendar years, inclusion of risk factors, selection of optimum degree of smoothing (bandwidth), hypothesis testing, ability to handle various types of outcome data, and use of standard software. The combination of mapping and statistical modeling provides a powerful tool for visualizing disease risk. Temporal-spatial analysis of the breast cancer epidemiological data will help researchers understand the role of environmental risk factors in the etiology of breast cancer. The application of GAMs and GIS to the casecontrol data will create breast cancer risk maps that are smoothed over time and space. The proposed research will track the magnitude, geographic size and location of elevated risk for the fifty years of residential history. The study will also investigate the spatial effects of temporal variables: residency duration, promoter periods, and non-upper Cape Cod residency. GIS will be used to overlay breast cancer maps and environmental data to generate new hypotheses for future research. The elevated risk of breast cancer on upper Cape Cod cannot be entirely explained by known risk factors. By learning where breast cancer "hot spots" are and if they grow, intensify, or move over time, researchers will have a better understanding of how environmental risk factors may be involved.

描述（由申请人提供）：尽管流行病学研究以调查可能的环境危险因素，但马萨诸塞州科德角乳腺癌率升高的原因仍然未知。上开普·科德（Cape Cod）的两项现有基于人群的乳腺癌病例对照研究（1983-1993）为所有受试者提供了地理编码的住宅历史和有关混杂因素的信息。结合两项研究创建了一个宝贵的数据集，用于从1943年至1993年对受试者住所的时间空间分析。 地理信息系统（GIS）允许在以前不可行的公共卫生研究中使用空间分析技术。广义添加剂模型（GAM）是绘制数据空间分布的有效方法，结合了许多理想的特征：地理位置和日历年的平滑，包括风险因素的选择，最佳平滑度（带宽），假设测试，能够处理各种类型的结果数据以及使用标准软件的使用能力。映射和统计建模的组合为可视化疾病风险提供了强大的工具。 乳腺癌流行病学数据的时间空间分析将帮助研究人员了解环境风险因素在乳腺癌病因中的作用。 GAM和GIS在Casecontrol数据中的应用将创建随着时间和空间的平滑乳腺癌风险图。拟议的研究将跟踪五十年住宅历史的风险升高的幅度，地理规模和位置。该研究还将研究时间变量的空间效应：居住持续时间，启动子周期和非欧普角鳕鱼居住。 GIS将用于覆盖乳腺癌图和环境数据，以生成新的假设供未来的研究。 上开普敦角上乳腺癌的风险升高不能完全通过已知危险因素来解释。通过学习乳腺癌的“热点”在哪里，如果它们随着时间的流逝而成长，加剧或移动，研究人员将更好地了解如何参与环境风险因素。