NCT03770351

Early Prostate Cancer: Predicting Treatment Response

Precision Medicine for Early Prostate Cancer: Integrating Biological and Patient Complexity Variables to Predict Treatment Response

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 693 (estimated)
• Sponsor: University of California, Irvine · Academic / Other
• Sex: Male
• Age: 18 Years – 90 Years
• Healthy volunteers: Not accepted

Summary

This study will replicate/validate the risk prediction model developed for the Comparative Effectiveness Analysis of Surgery and Radiation (CEASAR) study in a more diverse patient population to assess generalizability of the model as well as evaluate the relative contribution of the Decipher Prostate Cancer Test and ProstateNext Test from Ambry Genetics, to the risk prediction model for estimating treatment outcomes, and thereby improve personalization of treatment options.

Detailed description

The study will contribute a replicable model for improving risk prediction from patient characteristics, clinical severity indicators, and genomic tests to aid in personalizing treatment. The proposed registry would also allow future comparisons of the gene expression used in other competing commercial test. The addition of the suggested genomic classifier and its associations with other patient and clinical characteristics will enhance the ability of future studies, analogous to CEASAR, to accurately predict the risk of tumor aggressiveness in prostate cancer.

Conditions

• Prostate Cancer

Timeline

• Start date: 2017-01-01
• Primary completion: 2021-07-01
• Completion: 2021-07-01
• First posted: 2018-12-10
• Last updated: 2021-04-09

Locations

5 sites across 1 country: United States