This trial studies the side effects and best way to perform genetic testing in predicting biomarkers of recurrence in patients with prostate cancer undergoing surgery. Collecting and storing samples of tissue, blood, and other body fluids from patients to test in the laboratory and collecting information about the patient's health and treatment may help doctors learn more about cancer and help predict the recurrence of prostate cancer
PRIMARY OBJECTIVES: I. To explore the performance of these models in predicting the likelihood of biochemical recurrence (BCR). SECONDARY OBJECTIVES: I. To explore the performance of these models in predicting upgrading and upstaging prior to surgery. II. To explore the performance of these models in improving risk stratification among patients eligible for active surveillance. III. To determine whether prostatic massage or surgery raises the count of circulating tumor cells (CTC) in post-digital rectal exam (DRE) blood specimens. OUTLINE: Patients receive prostatic massage and undergo a digital rectal exam (DRE). Laboratory assessments are performed and blood samples are collected for molecular biology testing. On the day of the scheduled prostatectomy, a second blood collection is performed prior to surgery.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
1,045
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
City of Hope Medical Center
Duarte, California, United States
Performance of these models in predicting the likelihood of BCR
Logistic regression and artificial neural networks will be used.
Time frame: Visit 2 (intraoperative setting)
Comparison of the performance in these models in predicting upgrading and upstaging prior to surgery
Logistic regression and artificial neural networks will be used.
Time frame: Visit 2 (intraoperative setting)
Comparison of the performance of these models in improving risk stratification among patients eligible for active surveillance
Logistic regression and artificial neural networks will be used.
Time frame: Visit 2 (intraoperative setting)
Determination whether prostatic massage or surgery raises the count of circulating tumor cells (CTCs) in post-DRE blood specimens
Logistic regression and artificial neural networks will be used.
Time frame: Visit 2 (intraoperative setting)
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Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery