Zhang Hong, Zeng Donglin, Olschwang Sylviane, Yu Kai
Institute of Biostatistics, School of Life Science, Fudan University, P.R.C ; Division of Cancer Epidemiology and Genetics, National Cancer Institute, U.S.A.
J Stat Plan Inference. 2013 Feb;143(2):368-377. doi: 10.1016/j.jspi.2012.08.006.
A formal semiparametric statistical inference framework is proposed for the evaluation of the age-dependent penetrance of a rare genetic mutation, using family data generated under a case-family design, where phenotype and genotype information are collected from first-degree relatives of case probands carrying the targeted mutation. The proposed approach allows for unobserved risk factors that are correlated among family members. Some rigorous large sample properties are established, which show that the proposed estimators were asymptotically semi-parametric efficient. A simulation study is conducted to evaluate the performance of the new approach, which shows the robustness of the proposed semiparamteric approach and its advantage over the corresponding parametric approach. As an illustration, the proposed approach is applied to estimating the age-dependent cancer risk among carriers of the MSH2 or MLH1 mutation.
本文提出了一个形式化的半参数统计推断框架，用于评估罕见基因突变的年龄依赖性外显率，该框架使用在病例-家系设计下生成的家系数据，其中从携带目标突变的病例先证者的一级亲属中收集表型和基因型信息。所提出的方法允许存在家庭成员间相关的未观察到的风险因素。建立了一些严格的大样本性质，表明所提出的估计量是渐近半参数有效的。进行了一项模拟研究以评估新方法的性能，该研究表明所提出的半参数方法的稳健性及其相对于相应参数方法的优势。作为一个例证，所提出的方法被应用于估计MSH2或MLH1突变携带者中与年龄相关的癌症风险。
