Abbreviated Name

PASS

Lead Investigator

Lin UW, Daniel W. — University of Washington

Coordinating Investigator

Zheng, Yingye — Fred Hutchinson Cancer Center

Involved Investigators

• Carroll, Peter R. — University of California San Francisco
• Chesnut, Gregory — Center for Prostate Disease Research Uniformed Services University of the Health Sciences and the Walter Reed National Military Medical Center
• Martin, Frances — Eastern Virginia Medical School
• Gleave, Martin — University of British Columbia
• Cooperberg, Matthew — SF VA
• Digel, Jon — Fred Hutchinson Cancer Center
• Wei, John — University of Michigan Recruiting
• Wagner, Andrew — Beth Israel Deaconess Medical Center
• Lin VA, Daniel W. — VA Medical Center Seattle
• Lin UW, Daniel W. — University of Washington
• Brooks, James D. — Stanford University Medical Center
• Listwin, Don — Canary Foundation
• Nelson, Peter S — Fred Hutchinson Cancer Center
• Sanda, Martin — Emory University School of Medicine
• Leach, Robin J — University of Texas Health Science Center at San Antonio
• McKenney, Jesse — Cleveland Clinic
• Srivastava, Sudhir — National Cancer Institute
• Zheng, Yingye — Fred Hutchinson Cancer Center

Abstract

Primary Objective: To discover and confirm biomarkers that predict aggressive disease as defined by pre-specified histological, PSA, clinical criteria, or outcomes based on these variables. Secondary Objectives: To determine the proportion of patients on active surveillance who progress based on the above criteria. To determine the clinical predictors of disease progression. To measure the recurrence-free, disease-specific, and overall survival of men on active surveillance for clinically localized prostate cancer.

Aims

Discover and confirm biomarkers that predict aggressive disease as defined by pre-specified histological, PSA, clinical criteria, or outcomes based on these variables.

Analytic Method

The primary objective of this repository is to discover and validate biomarkers predicting aggressive disease, with emphasis on validation. The sample size and power is based on validation of a biomarker after its initial discovery. Since this cohort of men has already elected AS, a desirable biomarker should have high specificity so that clinicians will minimize the proportion of those men advised for more aggressive treatment, while still identifying the subset of men with high risk for progression. Therefore, we evaluate the sensitivity of a biomarker predicting aggressive disease at 95% specificity. We assume the threshold for 95% specificity needs to be estimated from this study, i.e., there is no pre-fixed threshold. This is more realistic because estimating the threshold usually requires a large study. The proportion of disease progression at 3 and 5 years from diagnosis is estimated at 25% and 33%. We want 90% power to confirm a sensitivity better than 10% (unacceptable) if the true sensitivity is 30% or better, at 95% specificity. Point estimate of sensitivity, specificity, and threshold and their 95% confidence intervals will be calculated. The sample size also depends on the slope of Receiver Operating Characteristic (ROC) curve at 95% specificity, usually quite steep when specificity is near 100%. We used 4 as the slope parameter for power analysis. Based on above assumptions, for a cohort with at least 3 years follow up, this study requires 100 men with disease progression and 300 men without progression, totally n=400. For a cohort with at least 5 years follow up, this study requires 125 men with progression and 250 men without progression, total n=375. Therefore, the total needed person-years follow up should be 375*5=1,875. The estimated number of patients elected for AS is about 350 in five sites combined. Given a conventional 25% recruitment rate, we expect 100 patients per year accrual. With 25% loss of follow-up, we estimate that each year’s 100 recruited men will finally contribute 375 person-years by the end of 5 years. It should be noted that we need full 5 years follow up to ensure that the men who had not progressed are indeed non-progressors, not false negatives. By the same reason, men after 5-years follow up will contribute little to the total person-years follow up because their risk of progression is felt to be low. Therefore, the study needs continuing 5 years recruitment and subsequent 5-years follow up with minimum 100 recruitment per year and a minimum 75% follow up rate.

Outcome

Primary Objective: To discover and confirm biomarkers that predict aggressive disease as defined by pre-specified histological, PSA, clinical criteria, or outcomes based on these variables. Secondary Objectives: To determine the proportion of patients on active surveillance who progress based on the above criteria. To determine the clinical predictors of disease progression. To measure the recurrence-free, disease-specific, and overall survival of men on active surveillance for clinically localized prostate cancer.

Publications

• Urinary TMPRSS2:ERG and PCA3 in an active surveillance cohort: results from a baseline analysis in the Canary Prostate Active Surveillance Study.

Biomarkers

• PCA3
• TMPRSS2:ERG

Data Collections

• No data collections available at this time for this protocol.

Start Date

Dec 19 2007

Estimated Finish Date

Dec 19 2010

Protocol ID

195

Protocol Type

Reference Set

Fields of Research

• Proteomics

Collaborative Group

Prostate and Urologic Cancers Research Group

Cancer Types

• Malignant neoplasm of prostate

Phased Status

2