RESEARCH IN BIOSTATISTICAL METHODOLOGY AND MATHEMATICAL MODELING

生物统计方法和数学建模研究

• 批准号: 6161594
• 负责人: C C BROWN
• 金额: --
• 依托单位: DIVISION OF CANCER PREVENTION AND CONTROL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6161594
• 关键词: carcinogenesis; clinical research; data collection methodology /evaluation; diet; human data; mathematical model; model design /development; neoplasm /cancer epidemiology; nutrition aspect of cancer; nutrition related tag; protooncogene; statistics /biometry

Different statistical methods are currently being used to analyze epidemiologic studies of diet and disease. This research project is examining the statistical properties of these methods. During the past year, two papers were written on new statistical models for incorporating measurement error in dietary intake and the application of these models to data from several dietary calibration studies. The Armitage-Doll mathematical model of carcinogenesis is being applied to experimental data on p53-knockout mice. Preliminary analyses indicate that inhibition of the normal p53 gene's tumor suppressor function by knocking out both alleles of the gene is consistent with 1 or 2 "stages" in the cancer process. Experimental data on hemizygotes with only one allele knocked out are being collected for additional analyses. New statistical methods for detection and inference of disease clusters are being developed. Previously proposed methods have been tests for overall clustering and do not have the ability to identify the location of clusters. The properties of a spatial scan statistic which takes into account the nonhomogeneous population densities as well as confounding variables have been evaluated. The statistic both tests for the location of clusters and tests for their statistical significance, and thus can be used both to evaluate cluster alarms and for routine surveillance. The spatial scan statistic has also been extended to study space-time clusters in addition to purely spatial ones. Copies of software related to this project are available on a web page: http://dcp.nci.nih.gov/BB/SaTScan.html.

目前正在使用不同的统计方法来分析 饮食与疾病的流行病学研究。这项研究项目是 检查这些方法的统计特性。在过去 年，就新的统计模型撰写了两篇论文 膳食摄入量的测量误差及其模型的应用 来自几项饮食校正研究的数据。 癌症发生的Armitage-Doll数学模型正在被应用 关于p53基因敲除小鼠的实验数据。初步分析表明 抑制正常P53基因的肿瘤抑制功能 敲除该基因的两个等位基因与1或2个“阶段”相一致。 在癌症的过程中。只有一个的半合子的实验数据 被敲除的等位基因正在被收集以进行进一步的分析。 疾病聚集性检测和推断的新统计方法 正在开发中。之前提出的方法已经进行了测试 整体群集化，并且无法识别位置 星团的数量。空间扫描统计量的属性考虑到 考虑到人口密度的不均匀以及混杂 已经对变量进行了评估。这两个统计数据都测试了该位置 对其统计意义进行分类和检验，因此可以 既可用于评估集群警报，也可用于常规监视。这个 空间扫描统计也被扩展到研究空间-时间 除了纯空间的集群外，还有其他的集群。相关软件的副本 此项目的详细信息可在网页上找到： Http://dcp.nci.nih.gov/BB/SaTScan.html.