Validation of Digital Morphometry for Cancer Risk in Benign Prostate Biopsies
| Status: | Active, not recruiting |
|---|---|
| Conditions: | Prostate Cancer, Cancer |
| Therapuetic Areas: | Oncology |
| Healthy: | No |
| Age Range: | 50 - 75 |
| Updated: | 11/8/2017 |
| Start Date: | September 2011 |
| End Date: | July 2021 |
R01 CA155301: Validation of Digital Morphometry for Cancer Risk in Benign Prostate Biopsies
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.
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.
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:
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University of Illinois at Chicago A major research university in the heart of one of...
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