Longitudinal Prostate cancer prediction

Principal Investigator

Name
Jonathan Gelfond

Degrees
MD, PhD

Institution
UT Health Science Center

Position Title
Associate Professor

Email
gelfondjal@uthscsa.edu

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-135

Initial CDAS Request Approval
Mar 16, 2015

Title
Longitudinal Prostate cancer prediction

Summary
We will develop a model that includes a time-to-event outcome. We will apply this model to prostate cancer detection within prospective study of a multi-ethnic cohort of >50,000 men without prostate cancer followed over the years. Biomarkers were measured along with clinical predictors of prostate cancer risk such as ethnicity, family history, and age. If the operating characteristics are adequate we will add the new method to a risk-assessment tool.

Aims

1a: Multivariate modeling of clinic visit data, with time-to-cancer detection will better predict than current methods.
2a. Extend to this model to multivariate modeling of related preclinical data so that we can can best characterize the effects of drugs on the aging process.

Collaborators

Donna Ankerst (UT Health Science Center)
Ian Thompson (UT Health Science Center)