  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.
