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Bayesian Semiparametric Estimation of Cancer-Specific Age-at-Onset Penetrance With Application to Li-Fraumeni Syndrome
- Shin, Seung Jun;
- Yuan, Ying;
- Strong, Louise C.;
- Bojadzieva, Jasmina;
- Wang, Wenyi
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10SCOPUS
10초록
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
- 제목
- Bayesian Semiparametric Estimation of Cancer-Specific Age-at-Onset Penetrance With Application to Li-Fraumeni Syndrome
- 저자
- Shin, Seung Jun; Yuan, Ying; Strong, Louise C.; Bojadzieva, Jasmina; Wang, Wenyi
- 발행일
- 2019-04-03
- 유형
- Article
- 권
- 114
- 호
- 526
- 페이지
- 541 ~ 552