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.
Original language | English |
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Pages (from-to) | 541-552 |
Number of pages | 12 |
Journal | Journal of the American Statistical Association |
Volume | 114 |
Issue number | 526 |
DOIs | |
Publication status | Published - 2019 Apr 3 |
Keywords
- Cancer-specific age-at-onset penetrance
- Competing risk
- Family-wise likelihood
- Gamma frailty model
- Li-Fraumeni syndrome
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty