Risk assessment of multistate progression of breast tumor with state-dependent genetic and environmental covariates

Yi Ying Wu, Ming Fang Yen, Cheng Ping Yu, Hsiu Hsi Chen

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Few studies have focused on the different roles risk factors play in the multistate temporal natural course of breast cancer. We proposed a three-state Markov regression model to predict the risk from free of breast cancer (FBC) to the preclinical screen-detectable phase (PCDP) and from the PCDP to the clinical phase (CP). We searched the initiators and promoters affecting onset and subsequent progression of breast tumor to build up a three-state temporal natural history model with state-dependent genetic and environmental covariates. This risk assessment model was applied to a 1 million Taiwanese women cohort. The proposed model was verified by external validation with another independent data set. We identified three kinds of initiators, including the BRCA gene, seven single nucleotides polymorphism, and breast density. ER, Ki-67, and HER-2 were found as promoters. Body mass index and age at first pregnancy both played a role. Among women carrying the BRCA gene, the 10-year predicted risk for the transition from FBC to CP was 25.83%, 20.31%, and 13.84% for the high-, intermediate-, and low-risk group, respectively. The corresponding figures were 1.55%, 1.22%, and 0.76% among noncarriers. The mean sojourn time of staying at the PCDP ranged from 0.82 years for the highest risk group to 6.21 years for the lowest group. The lack of statistical significance for external validation (x(4)2=5.30,p=0.26) revealed the adequacy of our proposed model. The three-state model with state-dependent covariates of initiators and promoters was proposed for achieving individually tailored screening and also for personalized clinical surveillance of early breast cancer.

Original languageEnglish
Pages (from-to)367-379
Number of pages13
JournalRisk Analysis
Volume34
Issue number2
DOIs
Publication statusPublished - Feb 2014

Fingerprint

Risk assessment
Tumors
Breast Neoplasms
Genes
Natural History
Single Nucleotide Polymorphism
Nucleotides
Polymorphism
Body Mass Index
Screening
Pregnancy

Keywords

  • Multistate multifactorial model
  • Translational research

ASJC Scopus subject areas

  • Physiology (medical)
  • Safety, Risk, Reliability and Quality

Cite this

Risk assessment of multistate progression of breast tumor with state-dependent genetic and environmental covariates. / Wu, Yi Ying; Yen, Ming Fang; Yu, Cheng Ping; Chen, Hsiu Hsi.

In: Risk Analysis, Vol. 34, No. 2, 02.2014, p. 367-379.

Research output: Contribution to journalArticle

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