Validation of Digital Morphometry for Cancer Risk in Benign Prostate Biopsies

University of Illinois at Chicago139 enrolled

Overview

The goal of this study is to apply cutting-edge imaging approaches, incorporating machine-learning for pattern recognition and multispectral analysis, to the development and validation of intermediate endpoint biomarkers in benign tissue that characterize the response to 5α-reductase inhibitor chemoprevention as well as the risk of prostate cancer among men with negative biopsies.

Study Type

OBSERVATIONAL

Enrollment

139

Conditions

Prostate Cancer

Interventions

DutasterideDRUG

0.5 mg daily

PlaceboDRUG

Placebo Comparator

Eligibility

Sex: MALEMin age: 50 YearsMax age: 75 Years

Medical Language ↔ Plain English

Inclusion Criteria: * completed REDUCE trial (Year 4 exit biopsy with blocks and HE slides available; i.e., U.S. participants only) * compliant with assigned treatment based on either: (dutasteride group) at least 3 post-baseline serum DHT levels ≥ 50% lower than baseline, or (placebo group) at least 3 post-baseline serum DHT levels with none showing ≥ 50% decrease from baseline Exclusion Criteria: * N/A

Locations (1)

University of Illinois at Chicago

Chicago, Illinois, United States

Outcomes

Primary Outcomes

Effects of dutasteride (vs. placebo) using multi-feature scores derived from digital image analysis on both nuclear and architectural features in benign prostate tissue.

Time frame: Year 4

Secondary Outcomes

Multivariable treatment-response score between subjects who develop PCa while on dutasteride and those who do not.

Time frame: Year 4

Magnitude of association between nuclear phenotype in benign biopsies, and subsequent risk of PCa in untreated men at elevated risk.

Time frame: Year 4

Data from ClinicalTrials.gov

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