Abbreviated Name

Pro-PSA

Lead Investigator

Chan, Daniel — Johns Hopkins Medical Institutions

Coordinating Investigator

Feng, Ziding — Fred Hutchinson Cancer Center

Involved Investigators

• Feng, Ziding — Fred Hutchinson Cancer Center
• — Johns Hopkins University Department of Urology
• Wagner, Andrew — Beth Israel Deaconess Medical Center
• Chan, Daniel — Johns Hopkins Medical Institutions
• Leach, Robin J — University of Texas Health Science Center at San Antonio
• Sanda, Martin — Emory University

Abstact

see Publication

Aims

Secondary Objectives – (1) To determine if [-2]proPSA is complementary to other PSA derivatives in a multi-marker model to improve the diagnosis and risk assessment of prostate cancer and reduce unnecessary biopsies, (2) To validate the serum %[-2]proPSA marker for the improvement of diagnosis and risk assessment of prostate cancer and reducing unnecessary biopsies in truncated PSA ranges such as 2-10 ng/mL PSA and 2-4 ng/mL PSA, (3) To determine if the [-2]proPSA marker or a combination of markers studied can aid in the identification of aggressive cancers as determined by Gleason score.

Analytic Method

The primary outcome analysis is to calculate the sensitivity corresponding to 70% specificity, i.e. ROC(0.30), and performing hypothesis testing against a null hypothesis of sensitivity=40%, i.e. ROC(0.30)=0.40. 95% confidence intervals will be calculated for ROC(0.30) as well as for the threshold corresponding to 70% sensitivity. The secondary outcome analysis is to calculate the specificity corresponding to 95% sensitivity and its threshold. Hypothesis testing will be conducted against the null hypothesis of specificity 5%. 95% confidence intervals will be calculated for ROC-1(0.95) as well as for the threshold corresponding to 95% sensitivity. Other exploratory analyses will be performed to examine the complementary properties of %proPSA with other clinical variables (age, race, and family history, DRE) and other PSA derivatives (PSA and fPSA). Logistic regression with forward model selection will be used to combine the markers and clinical variables. The ROC curve of the predicted score will be plotted and compared to that of the model using clinical variables and existing PSA and its derivatives but without %proPSA. These analyses will be performed for the whole group, for the group with PSA 2-10 ng/mL, and for the group with PSA 2-10 ng/mL and without suspicious DRE.

Biomarkers

• KLK4
• proPSA

Data Collections

• No data available at this time for this protocol

Protocol ID

193

Protocol Type

Validation

Field of Research

Proteomics

Collaborative Group

Prostate and Urologic Cancers Research Group

Cancer Types

• Malignant neoplasm of prostate

Phased Status

2