ABSTRACT Penetrance, which plays a key role in genetic research, is defined as the proportion of individuals with the genetic variants (i.e., genotype) that cause a particular trait and who have clinical symptoms of the trait (i.e., phenotype). We propose a Bayesian semiparametric approach to estimate the cancer-specific age-at-onset penetrance in the presence of the competing risk of multiple cancers. We employ a Bayesian semiparametric competing risk model to model the duration until individuals in a high-risk group develop different cancers, and accommodate family data using family-wise likelihoods. We tackle the ascertainment bias arising when family data are collected through probands in a high-risk population in which disease cases are more likely to be observed. We apply the proposed method to a cohort of 186 families with Li-Fraumeni syndrome identified through probands with sarcoma treated at MD Anderson Cancer Center from 1944 to 1982. Supplementary materials for this article are available online.

中文翻译：

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癌症特异性发病年龄外显率的贝叶斯半参数估计及其在 Li-Fraumeni 综合征中的应用

摘要 外显率在基因研究中发挥着关键作用，被定义为具有导致特定性状的遗传变异（即基因型）以及具有该性状临床症状（即表型）的个体的比例。我们提出了一种贝叶斯半参数方法来估计在多种癌症竞争风险存在的情况下癌症特定的发病年龄外显率。我们采用贝叶斯半参数竞争风险模型来模拟高风险群体中的个体患上不同癌症的持续时间，并使用家庭明智的可能性来适应家庭数据。我们解决了通过高危人群中的先证者收集家庭数据时产生的确定偏差，在高危人群中更有可能观察到疾病病例。我们将所提出的方法应用于 186 个 Li-Fraumeni 综合征家庭的队列，这些家庭是通过 1944 年至 1982 年在 MD 安德森癌症中心治疗的肉瘤先证者来确定的。本文的补充材料可在线获取。