TY - JOUR
T1 - Bayesian estimation of a semiparametric recurrent event model with applications to the penetrance estimation of multiple primary cancers in Li-Fraumeni syndrome
AU - Shin, Seung Jun
AU - Li, Jialu
AU - Ning, Jing
AU - Bojadzieva, Jasmina
AU - Strong, Louise C.
AU - Wang, Wenyi
N1 - © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
PY - 2020
Y1 - 2020
N2 - A common phenomenon in cancer syndromes is for an individual to have multiple primary cancers (MPC) at different sites during his/her lifetime. Patients with Li-Fraumeni syndrome (LFS), a rare pediatric cancer syndrome mainly caused by germlineTP53 mutations, are knownto have a higher probability of developing a second primary cancer than those with other cancer syndromes. In this context, it is desirable to model the development of MPC to enable better clinical management of LFS. Here, we propose a Bayesian recurrent event model based on a non-homogeneous Poisson process in order to obtain penetrance estimates forMPC related to LFS. We employed a familywise likelihood that facilitates using genetic information inherited through the family pedigree and properly adjusted for the ascertainment bias that was inevitable in studies of rare diseases by using an inverse probability weighting scheme. We applied the proposed method to data on LFS, using a family cohort collected through pediatric sarcoma patients at MDAnderson Cancer Center from 1944 to 1982. Both internal and external validation studies showed that the proposed model provides reliable penetrance estimates for MPC in LFS, which, to the best of our knowledge, have not been reported in the LFS literature.
AB - A common phenomenon in cancer syndromes is for an individual to have multiple primary cancers (MPC) at different sites during his/her lifetime. Patients with Li-Fraumeni syndrome (LFS), a rare pediatric cancer syndrome mainly caused by germlineTP53 mutations, are knownto have a higher probability of developing a second primary cancer than those with other cancer syndromes. In this context, it is desirable to model the development of MPC to enable better clinical management of LFS. Here, we propose a Bayesian recurrent event model based on a non-homogeneous Poisson process in order to obtain penetrance estimates forMPC related to LFS. We employed a familywise likelihood that facilitates using genetic information inherited through the family pedigree and properly adjusted for the ascertainment bias that was inevitable in studies of rare diseases by using an inverse probability weighting scheme. We applied the proposed method to data on LFS, using a family cohort collected through pediatric sarcoma patients at MDAnderson Cancer Center from 1944 to 1982. Both internal and external validation studies showed that the proposed model provides reliable penetrance estimates for MPC in LFS, which, to the best of our knowledge, have not been reported in the LFS literature.
KW - Age-at-onset penetrance
KW - Familywise likelihood
KW - Li-Fraumeni syndrome
KW - Multiple primary cancers
KW - Recurrent event model.
UR - http://www.scopus.com/inward/record.url?scp=85086883545&partnerID=8YFLogxK
U2 - 10.1093/BIOSTATISTICS/KXY066
DO - 10.1093/BIOSTATISTICS/KXY066
M3 - Article
C2 - 30445420
AN - SCOPUS:85086883545
SN - 1465-4644
VL - 21
SP - 467
EP - 482
JO - Biostatistics
JF - Biostatistics
IS - 3
ER -