MODIFIED SCORE METHODS FOR CANCER CASE-CONTROL STUDIES

癌症病例对照研究的改良评分方法

• 批准号: 3446852
• 负责人: JAMES B KAMPERT
• 金额: $ 5.75万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1986
• 资助国家: 美国
• 起止时间: 1986-09-15 至 1989-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3446852
• 关键词: breast neoplasms; cancer information system; cancer risk; computer simulation; mathematical model; neoplasm /cancer classification /staging

The proposed work will develop, evaluate, and apply new statistical methodology to analyze case-control data. The new methods are designed to efficiently and inexpensively combine multivariate data from numerous large strata in fitting general relative risk models. These methods appreciably curtail high computing costs in using large-scale (mainframe) computers, compared to existing methods. They significantly improve slow computing times in using smaller time-sharing minicomputers or microcomputers with limited addressable memory. The specific aims of the proposed work are: 1) to extend the newly developed method of modified-score logistic risk analysis to more general relative risk functions; 2) to develop and test improved estimators to reduce small-strata estimation bias and speed convergence to asymptotic behavior; 3) to develop methods to efficiently combine multivariate data from numerous large and small strate, with minimal bias and computational effort; 4) to develop analysis of residuals and measures of deviance for fitting nested models and indicating model departures; 50 to develop regression diagnostics for detecting outliers and data points with undue influence on parameter estimates; 6) to develop methods for estimating multivariate attributable risk in matched or stratified case-control data; and 7) to develop methods for classification and discrimination in these study designs. Monte-Carlo sampling experiments (computer simulations) using a variety of case-control study designs will be conducted to demonstrate the performance of the new methods in comparison to alternative methods. The new methodology will be used in fitting proportional hazards models to existing data for 1884 breast cancer patients and 3432 control patients in multivariate prediction of breast cancer risk. Attributable risk of breast cancer due to single and multiple factors in the presence of all others will be estimated. Multifactorial classification of women at high and low short-term and lifetime risk will be determined. Additivity and multiplicativity of risk predictors will be investigated. A portable, control-statement operated computer program to implement the new methodology will be developed and made available to others.

拟议的工作将开发、评估和应用新的统计数据， 方法学分析病例对照数据。 新方法旨在 有效且廉价地联合收割机将来自众多大型 层拟合一般相对风险模型。 这些方法明显 削减使用大型（主机）计算机的高计算成本， 与现有方法相比。 它们显著改善了慢速计算 使用小型分时微型计算机或微型计算机的时间 有限的可寻址内存。 拟议工作的具体目标是： 1)扩展了新开发的改进评分逻辑风险法 分析更一般的相对风险函数; 2）开发和测试 减少小层估计偏差和速度的改进估计器 收敛到渐近行为; 3）开发方法，以有效地 联合收割机将来自众多大小基板的多变量数据与 最小偏差和计算工作量; 4）开发残差分析 拟合嵌套模型和指示模型的离差度量 偏离; 50开发用于检测异常值的回归诊断， 对参数估计有不当影响的数据点; 6）开发 用于估计匹配或不匹配的多变量归因风险的方法 分层病例对照数据;和7）制定分类方法 和歧视。 蒙特-卡罗抽样实验（计算机模拟）使用各种 将进行病例对照研究设计，以证明性能 与替代方法相比，新方法。 新 方法将用于将比例风险模型拟合到现有的 1884名乳腺癌患者和3432名对照患者的数据， 乳腺癌风险的多变量预测。 乳腺的归因风险 癌症由于单一和多种因素的存在下，所有其他 将估计。 高收入和低收入妇女的多因素分类 将确定短期和终身风险。 可加性和 将研究风险预测因子的倍增性。 一种便携式， 控制语句操作的计算机程序，以实现新的 将制定方法并提供给其他人。