Chatterjee Nilanjan, Kalaylioglu Zeynep, Shih Joanna H, Gail Mitchell H
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, 6210 Executive Boulevard, Rockville, Maryland 20852, USA.
Biometrics. 2006 Mar;62(1):36-48. doi: 10.1111/j.1541-0420.2005.00442.x.
In case-control studies of inherited diseases, participating subjects (probands) are often interviewed to collect detailed data about disease history and age-at-onset information in their family members. Genotype data are typically collected from the probands, but not from their relatives. In this article, we introduce an approach that combines case-control analysis of data on the probands with kin-cohort analysis of disease history data on relatives. Assuming a marginally specified multivariate survival model for joint risk of disease among family members, we describe methods for estimating relative risk, cumulative risk, and residual familial aggregation. We also describe a variation of the methodology that can be used for kin-cohort analysis of the family history data from a sample of genotyped cases only. We perform simulation studies to assess performance of the proposed methodologies with correct and mis-specified models for familial aggregation. We illustrate the proposed methodologies by estimating the risk of breast cancer from BRCA1/2 mutations using data from the Washington Ashkenazi Study.
在遗传性疾病的病例对照研究中,通常会对参与研究的受试者(先证者)进行访谈,以收集有关其家族成员疾病史和发病年龄信息的详细数据。基因型数据通常从先证者那里收集,而不是从他们的亲属那里收集。在本文中,我们介绍了一种方法,该方法将先证者数据的病例对照分析与亲属疾病史数据的亲属队列分析相结合。假设对家庭成员中疾病的联合风险采用边际指定的多变量生存模型,我们描述了估计相对风险、累积风险和残余家族聚集性的方法。我们还描述了该方法的一种变体,可用于仅对基因型病例样本的家族史数据进行亲属队列分析。我们进行模拟研究,以评估所提出方法在家族聚集性模型正确和错误指定情况下的性能。我们使用华盛顿阿什肯纳齐研究的数据,通过估计BRCA1/2突变导致乳腺癌的风险来说明所提出的方法。