RESEARCH IN BIOSTATISTICAL METHODOLOGY AND MATHEMATICAL MODELING

生物统计方法和数学建模研究

• 批准号: 3874572
• 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/3874572
• 关键词: breast neoplasms; cancer information system; cancer prevention; cancer risk; carcinogenesis; carcinogenesis inhibitor; computer data analysis; computer simulation; drug resistance; human age group; human mortality; lung neoplasms; mathematical model; model design /development; neoplasm /cancer chemotherapy; neoplasm /cancer epidemiology; nutrition related tag; statistics /biometry; tobacco abuse

The purpose of this project is development of biostatistical methods and mathematical models appropriate for the analysis of epidemiologic and experimental studies related to cancer control and prevention. Many of the statistical problems being studied under this project are derived from the consultation activities of the Section. The proper time metric to be used when applying Cox regression techniques to analyze a cohort's cancer incidence over time is being studied by simulation methods. Data are being generated according to known cancer age-specific incidence and known mortality from all causes. The time metrics being studied are follow-up time from study initiation and age at risk. Different study durations are also being evaluated. In addition, different methods to properly estimate the effect of risk factors which are related to age at ascertainment are being evaluated. The assumption of "proportional hazards" is commonly made when analyzing survival in patients treated for cancer. The scale parameter in parametric models and the underlying hazard function in semi-parametric models are assumed to vary between patients only because of the risk factors included in the model. However, extraneous hazard rate heterogeneity can produce substantial deviations from this assumption. This research will fit a Gamma-mixture of Weibull models to estimate the degree of heterogeneity and its biasing effect on estimated parameters and on the hazard ratio. Methodology is being developed to calculate the necessary sample size n,m (n is the number of measuring devices and m is the number of items being measured) to test the hypothesis that the accuracy of a measuring device is acceptably large. The results will be used to develop sampling methods to evaluate the accuracy of the CIS.

这个项目的目的是开发生物统计方法和 适合于流行病学和疾病分析的数学模型 与癌症控制和预防相关的实验研究。许多人 本项目下正在研究的统计问题源自 该科的协商活动。 应用COX回归技术时应使用的适当时间度量 为了分析队列中一段时间内的癌症发病率， 模拟方法。数据是根据已知的癌症生成的 所有原因的特定年龄发病率和已知死亡率。时间 正在研究的指标是从研究开始的随访时间和年龄 风险。不同的学习时间也在评估中。此外, 正确估计风险因素影响的不同方法 正在对与确定年龄有关的问题进行评估。 在分析时，通常会提出“比例风险”的假设。 癌症治疗患者的存活率。参数中的Scale参数 半参数模型中的模型和基本风险函数是 假设患者之间的差异仅仅是因为包括的风险因素 在模型中。然而，外来的危险比率异质性可能会产生 与这一假设有很大偏离。这项研究将适用于 威布尔模型的伽马混合估计非均质程度和 它对估计参数和危险比的偏差影响。 正在开发方法来计算必要的样本量n，m (n是测量装置的数量，m是 测量)来检验测量装置的精度是 大得可以接受。这些结果将被用来制定抽样方法，以 评估CIS的准确性。