METHODS FOR AGE AT ONSET DATA IN GENETIC EPIDEMIOLOGY

描述：(改编自《调查者摘要》)长期目标 这项研究的重点是创建合理的方法，这将 促进研究遗传和环境因素在 癌症病因学。这项提议的短期目标是发展 基于人口的家庭首发年龄数据的统计方法 学习。这些方法解决了该领域的两个重要问题，即， 确定和丢失数据的问题。年龄的分析方法 由于审查制度的复杂性和 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，它收集了基于人口的 第一阶段指标对象及其危险因素和家族史， 收集索引对象亲属的风险因素在第二 阶段，最后收集选定家庭的血液/组织样本。在……里面 根据每个阶段，本提案的具体目标是 发展下列方法：1)AGEs的聚集分析 从第一阶段研究开始；2)分离和聚集相结合 第二阶段研究的发病年龄分析；以及3)合并 日本血吸虫病发病年龄的连锁、分离和聚集分析 第三阶段研究。还将开发用于合并丢失的方法 数据问题，包括以下内容：所有数据缺失风险因素 亲属；遗漏或错误测量索引对象的风险因素；失踪 或发病时年龄测量错误，尽管疾病发病已知；以及 疾病状态的错误分类。方法(1)-(3)将应用于 三组遗传流行病学数据。这些是以人口为基础的 早期乳腺癌的病例对照家系研究；一项基于卫生保健组织人群的研究 阿尔茨海默病的病例对照家族研究；以及一项基于人群的研究 卵巢癌病例对照家系研究。发病年龄为 将使用半参数建模和估计方程技术 对家庭内部相互关系的性质进行建模。方法将是 使用经验过程和其他统计手段进行了严格的研究。 将开发用户友好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.