RESEARCH IN BIOSTATISTICAL METHODOLOGY AND MATHEMATICAL MODELING

生物统计方法和数学建模研究

• 批准号: 3853359
• 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/3853359
• 关键词: cancer information system; cancer prevention; cancer risk; computer simulation; human age group; human mortality; mathematical model; model design /development; neoplasm /cancer epidemiology; prognosis; statistics /biometry

The purpose of this project is the development of biostatistical methods appropriate for epidemiologic and experimental studies related to cancer prevention and control. Poison regression methods are often used to analyze the relationship of a county's cancer mortality to its demographic, economic, and ecologic characteristics. Because of variability of cancer risk among members of the county's population, the Poison assumption is theoretically invalid. This research will evaluate the actual degree of intra-county temporal heterogeneity for the major cancer sites. 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. Only the scale parameter in parametric models and the proportionality parameter in semi-parametric models are assumed to vary among patients through their prognostic variables. Because extraneous hazard rate heterogeneity can produce substantial deviations from this assumption, this research will compare the fits of a Weibull model with a Gamma-mixture of Weibull models to estimate the degree of heterogeneity and its biasing effect on estimated parameters and on the hazard ratio.

该项目的目的是开发生物统计方法 适用于与癌症相关的流行病学和实验研究 预防和控制。 毒回归方法通常用于分析 县的癌症死亡率与其人口、经济和生态的关系 特征。 由于成员之间癌症风险的差异 就该县的人口而言，Poison 假设在理论上是无效的。 本研究将评估县内时间的实际程度 主要癌症部位的异质性。 应用 Cox 回归技术时要使用的适当时间度量 正在研究分析一个队列随时间的癌症发病率 模拟方法。 数据是根据已知的癌症生成的 特定年龄的发病率和已知的各种原因的死亡率。 时间 正在研究的指标是研究开始后的随访时间和年龄 风险。 不同的研究持续时间也正在评估中。 此外， 不同的方法来正确估计风险因素的影响 正在评估与确定年龄相关的问题。 在分析时通常会做出“比例风险”的假设 接受癌症治疗的患者的生存率。 仅尺度参数 参数模型和半参数中的比例参数 假设模型因患者的预后而异 变量。 因为外部危险率异质性会产生 与这一假设有很大偏差，本研究将比较 威布尔模型与威布尔模型伽玛混合的拟合来估计 异质性程度及其对估计参数的偏差影响 以及风险比。