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Longitudinal Prostate cancer prediction

Principal Investigator
Name
Jonathan Gelfond
Degrees
MD, PhD
Institution
UT Health Science Center
Position Title
Associate Professor
Email
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)