Dynamic Risk Prediction of Prostate Cancer Development Using Longitudinal Biomarkers of PSA

Principal Investigator

Name
Ming Wang

Degrees
Ph.D.

Institution
The Pennsylvania State University

Position Title
Associate Professor

Email
mwang@phs.psu.edu

About this CDAS Project

Study
PLCO (Learn more about this study)

Project ID
PLCO-775

Initial CDAS Request Approval
Apr 20, 2021

Title
Dynamic Risk Prediction of Prostate Cancer Development Using Longitudinal Biomarkers of PSA

Summary
The overall goal is to develop statistical modeling or data-science driven tools to obtain knowledge and insight from large and complex sets of prostate cancer data. We mainly focus on dynamic risk prediction of prostate cancer development using longitudinal biomarkers of PSA.

Aims

Because of the longitudinal follow-up on the biomarker of PSA and large sample size, we would like to perform the following aims:
• Develop prediction models for prostate cancer development and also the metastasis by considering PSA and other demographic/clinical/social economic data using the PLCO;
• Develop the models and toolbox/website to analyze newly diagnosis patients using PLCO newly diagnosed cancer patients. We can perform data cleaning, process, harmonization, summary statistics, and further clustering analysis to identify subtypes. In particular, we can consider prediction of (overall and cancer-specific) mortality for overall prostate cancer patients, and also the subcohort with metastatic prostate cancer patients only.
• Develop the models and toolbox/website for evaluation of the treatment information and treatment decision making that is of most importance and clinical impact.

Collaborators

Nicholas Zaorsky, Penn State College of Medicine
Alicia McDonald, Penn State College of Medicine