METHODS FOR AGE AT ONSET DATA IN GENETIC EPIDEMIOLOGY

描述：（改编自研究者摘要）长期目的 这项研究的一个重要方面是建立健全的方法， 促进研究遗传和环境因素在 癌症病因学 该提案的短期目标是发展 基于人群家庭发病年龄数据统计方法 问题研究 这些方法解决了该领域的两个重要问题，即， 数据缺失和数据缺失问题。 年龄分析方法 由于审查制度的复杂性， 可能的关联 为了避免确定问题，家庭研究 是通过多阶段设计进行的， 指标对象及其危险因素和家族史在第一阶段， 在第二阶段收集索引受试者亲属的风险因素， 阶段，最后从选定的家庭收集血液/组织样本。 在 根据每个阶段，本提案的具体目标是 为以下方面制定方法：1）年龄的汇总分析 在第一阶段研究开始时; 2）分离和聚集相结合 第二阶段研究的发病年龄分析;和3）合并 发病年龄的连锁、分离和聚集分析 第三阶段研究。 还将制定方法， 数据问题，其中包括： 亲属;索引受试者的风险因素缺失或测量错误;缺失 或者说，他是一个知道自己的年龄的人。 疾病状态的错误分类。 方法（1）-（3）将应用于 三个遗传流行病学数据集。 这是一个基于人口的 早期乳腺癌的病例对照家系研究 阿尔茨海默病的病例对照家庭研究;和基于人群的 卵巢癌的病例对照家系研究 发病年龄为 将使用半参数建模和估计方程技术 来模拟家庭内部相互关系的本质。 方法将是 使用经验过程和其他统计方法进行严格研究。 将开发方便用户的程序并向公众提供。

DESCRIPTION: (Adapted from Investigator's Abstract) The long-term objective of this research is the creation of sound methodologies which will facilitate studying the role of both genetic and environmental factors in cancer etiology. The short-term goal of this proposal is to develop statistical methods for age at onset data from population-based family studies. These methods address two important problems in the field, namely, ascertainment and the missing data problem. Methods for analysis of age at onset are not well established, due to the complexity of censorship and possible correlations. To avoid the ascertainment problem, family studies are conducted through the multistage design, which collects population-based index subjects and their risk factors and family history at the first stage, collects risk factors for the relatives of index subjects at the second stage, and finally collects blood/tissue samples from selected families. In accordance with each stage, the specific aims of this proposal are development of methods for the following: 1) aggregation analysis of ages at onset from the first stage study; 2) combined segregation and aggregation analysis of ages at onset from the second stage study; and 3) combined linkage, segregation and aggregation analysis of ages at onset from the third stage study. Methods will also be developed for incorporating missing data problems, which include the following: missing risk factors for all relatives; missing or mismeasured risk factors for index subjects; missing or mismeasured age at onset though disease onset is known; and misclassification of disease status. Methods (1) - (3) will be applied to three genetic epidemiologic datasets. These are a population-based case-control family study of early breast cancer; an HMO population-based case-control family study of Alzheimer's disease; and a population-based case-control family study of ovarian cancer. The age at onset will be modeled semiparametrically and estimating equations techniques will be used to model the nature of correlations within families. The methods will be studied rigorously using empirical processes and other statistical devices. User-friendly programs will be developed and made available to the public.