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Geostatistical software for the analysis of individual-level epidemiologic data

用于分析个人流行病学数据的地统计软件

基本信息

批准号：
7399698
负责人：
PIERRE E GOOVAERTS
金额：
$ 9.98万
依托单位：
BIOMEDWARE
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-09-25 至 2009-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7399698
关键词：
Address Adoption Area Attention Behavioral Breast Categories Cluster Analysis Computer software Condition Data Detection Development Diagnostic Neoplasm Staging Disclosure Disease Disease Clusterings Ecological Bias Economic Conditions Educational workshop Environmental and Occupational Exposure Evaluation Event Fertilization Fostering Grant Health Health Sciences Health Status Imagery Incidence Individual Intelligence International Investigation Lead Link Location Malignant Neoplasms Malignant neoplasm of prostate Maps Measures Methodology Methods Michigan Minority Morbidity - disease rate Mortality Map Nature Numbers Outcome Patients Pattern Performance Phase Population Population Density Population Heterogeneity Population Sizes Probability Process Publications Purpose Race Rate Relative Risks Research Resources Risk Risk Factors Science Scientist Screening procedure Shapes Small Business Funding Mechanisms Small Business Innovation Research Grant Stage at Diagnosis Staging Statistical Methods Sum Survival Rate System Techniques Testing Time Tumor stage Uncertainty United States United States National Institutes of Health Ursidae Family Validity of Results Variant anticancer research base cancer diagnosis cancer prevention density design geographic difference health disparity improved innovation medically underserved member mortality novel patient privacy prevent prototype reconstruction simulation size socioeconomics statistics theories tool

项目摘要

DESCRIPTION (provided by applicant): The overall objective of this project is to develop the first GIS-based software to offer tools that are specifically designed for the geostatistical analysis of both aggregated and individual-level health data, providing: description of spatial patterns of cancer incidence and mortality rates and identification of scales of variability, spatial interpolation of individual-level data to create isopleth maps of relative risk, identification of clusters and hotspots of significantly high or low incidence or mortality rates, detection of significant discrepancies between health outcomes for different ethnic or racial groups (health disparities), and visualization of changes in disparity through time. This product will allow the investigation of geographic and ethnic variations in cancer stage at diagnosis and survival data, and the exploration of relationships between health outcomes and potential factors, such as environmental and occupational exposures, socio-economic conditions, proximity to screening centers, leading to: (1) a better understanding of the causes underlying observed geographic and racial disparities in cancer incidence, mortality and survival, and (2) long-term quantification of the benefits of current strategies for reducing the disproportionate incidence of cancer morbidity and mortality among minorities and the medically underserved in the United States. Instructional materials will be developed to promote the use of this relatively new methodology among health scientists. Phase I of the project will: risk maps from individual-level data and statistical tests to detect significant differences in cancer rates among sub-populations and across space. into the software: TerraSeer Space-Time Intelligence System(tm) (STIS(tm)). geographical and racial disparities. The substantial benefit of this research is its utility in accessing, linking, mapping and analyzing diverse population-based and individual-level data including cancer vital events and measures of socioeconomic, demographic, behavioral and environmental conditions. The methods developed in this project will help understanding the causes underlying the disparities in cancer incidence, mortality and morbidity observed across space and among sub-populations, as well as lead to a better assessment of the benefits of current strategies for reducing these disparities.

描述（由申请方提供）：该项目的总体目标是开发第一个基于地理信息系统的软件，提供专门为综合和个人层面健康数据的地理统计分析而设计的工具，提供：描述癌症发病率和死亡率的空间模式，确定变异尺度，对个人数据进行空间插值，以绘制相对风险的等值线图，确定发病率或死亡率显著较高或较低的集群和热点，检测不同族裔或种族群体健康结果之间的显著差异（健康差异），以及可视化差异随时间的变化。该产品将允许调查诊断时癌症阶段和生存数据的地理和种族差异，并探索健康结果与潜在因素之间的关系，例如环境和职业暴露，社会经济条件，与筛查中心的接近程度，从而导致：（1）更好地理解在癌症发病率、死亡率和存活率方面观察到的地理和种族差异的根本原因，以及（2）长期量化当前策略对降低美国少数民族和医疗服务不足人群癌症发病率和死亡率不成比例的影响。将编制教学材料，以促进卫生科学家使用这种相对较新的方法。该项目的第一阶段将：根据个人层面的数据和统计测试绘制风险图，以检测各亚群体和各空间癌症发病率的显著差异。TerraSeer时空智能系统（TM）（STIS（TM））。地理和种族差异。这项研究的实质性好处是它在访问，链接，映射和分析不同的基于人群和个人水平的数据，包括癌症生命事件和社会经济，人口统计，行为和环境条件的措施的效用。该项目开发的方法将有助于了解在不同空间和不同亚人群中观察到的癌症发病率、死亡率和发病率差异的根本原因，并有助于更好地评估目前减少这些差异的战略的益处。