Bayesian Semiparametric Estimation of Cancer-Specific Age-at-Onset Penetrance With Application to Li-Fraumeni Syndrome

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초록

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.

키워드

Cancer-specific age-at-onset penetranceCompeting riskFamily-wise likelihoodGamma frailty modelLi-Fraumeni syndromeCOMPETING RISKSBREAST-CANCERP53 MUTATIONSGENE-CHARACTERIZATIONFIT TESTSMODELSPEDIGREEGOODNESSFAMILYCOHORT
제목
Bayesian Semiparametric Estimation of Cancer-Specific Age-at-Onset Penetrance With Application to Li-Fraumeni Syndrome
저자
Shin, Seung JunYuan, YingStrong, Louise C.Bojadzieva, JasminaWang, Wenyi
DOI
10.1080/01621459.2018.1482749
발행일
2019-04-03
유형
Article
저널명
Journal of the American Statistical Association
114
526
페이지
541 ~ 552