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Objective To examine the ability of a novel live primary-cell phenotypic (LPCP) test to predict postsurgical adverse pathology (P-SAP) features and risk stratify patients based on SAP features in a blinded study utilizing radical prostatectomy (RP) surgical specimens. Methods Two hundred fifty-one men undergoing RP were enrolled in a prospective, multicenter (10), and proof-of-concept study in the United States. Fresh prostate samples were taken from known areas of cancer in the operating room immediately after RP. Samples were shipped and tested at a central laboratory. Utilizing the LPCP test, a suite of phenotypic biomarkers was analyzed and quantified using objective machine vision software. Biomarkers were objectively ranked via machine learning-derived statistical algorithms (MLDSA) to predict postsurgical adverse pathological features. Sensitivity and specificity were determined by comparing blinded predictions and unblinded RP surgical pathology reports, training MLDSAs on 70% of biopsy cells and testing MLDSAs on the remaining 30% of biopsy cells across the tested patient population. Results The LPCP test predicted adverse pathologies post-RP with area under the curve (AUC) via receiver operating characteristics analysis of greater than 0.80 and distinguished between Prostate Cancer Grade Groups 1, 2, and 3/Gleason Scores 3 + 3, 3 + 4, and 4 + 3. Further, LPCP derived-biomarker scores predicted Gleason pattern, stage, and adverse pathology with high precision—AUCs>0.80. Conclusion Using MLDSA-derived phenotypic biomarker scores, the LPCP test successfully risk stratified Prostate Cancer Grade Groups 1, 2, and 3 (Gleason 3 + 3 and 7) into distinct subgroups predicted to have surgical adverse pathologies or not with high performance (>0.85 AUC).

Objectives To evaluate the impact of a genomic classifier (GC) test for predicting metastasis risk after radical prostatectomy (RP) on urologists' decision-making about adjuvant treatment of patients with high-risk prostate cancer. Subjects and Methods Patient case history was extracted from the medical records of each of the 145 patients with pT3 disease or positive surgical margins (PSMs) after RP treated by six high-volume urologists, from five community practices. GC results were available for 122 (84%) of these patients. US board-certified urologists (n = 107) were invited to provide adjuvant treatment recommendations for 10 cases randomly drawn from the pool of patient case histories. For each case, the study participants were asked to make an adjuvant therapy recommendation without (clinical variables only) and with knowledge of the GC test results. Recommendations were made without knowledge of other participants' responses and the presentation of case histories was randomised to minimise recall bias. Results A total of 110 patient case histories were available for review by the study participants. The median patient age was 62 years, 71% of patients had pT3 disease and 63% had PSMs. The median (range) 5-year predicted probability of metastasis by the GC test for the cohort was 3.9 (1–33)% and the GC test classified 72% of patients as having low risk for metastasis. A total of 51 urologists consented to the study and provided 530 adjuvant treatment recommendations without, and 530 with knowledge of the GC test results. Study participants performed a mean of 130 RPs/year and 55% were from community-based practices. Without GC test result knowledge, observation was recommended for 57% (n = 303), adjuvant radiation therapy (ART) for 36% (n = 193) and other treatments for 7% (n = 34) of patients. Overall, 31% (95% CI: 27–35%) of treatment recommendations changed with knowledge of the GC test results. Of the ART recommendations without GC test result knowledge, 40% (n = 77) changed to observation (95% CI: 33–47%) with this knowledge. Of patients recommended for observation, 13% (n = 38 [95% CI: 9–17%]) were changed to ART with knowledge of the GC test result. Patients with low risk disease according to the GC test were recommended for observation 81% of the time (n = 276), while of those with high risk, 65% were recommended for treatment (n = 118; P < 0.001). Treatment intensity was strongly correlated with the GC-predicted probability of metastasis (P < 0.001) and the GC test was the dominant risk factor driving decisions in multivariable analysis (odds ratio 8.6, 95% CI: 5.3–14.3%; P < 0.001). Conclusions Knowledge of GC test results had a direct effect on treatment strategies after surgery. Recommendations for observation increased by 20% for patients assessed by the GC test to be at low risk of metastasis, whereas recommendations for treatment increased by 16% for patients at high risk of metastasis. These results suggest that the implementation of genomic testing in clinical practice may lead to significant changes in adjuvant therapy decision-making for high-risk prostate cancer.

To assess the effect of an individualized genomic classifier (GC) test, for predicting metastasis following radical prostatectomy (RP), on urologists' adjuvant treatment decisions when caring for high-risk patients.Data were submitted by US board-certified urologists in community practices (n = 15), who ordered the GC test for 146 prostate cancer patients with adverse pathologic features following RP (i.e., pathologic stage pT3 or positive surgical margins). Treatment recommendations were reported using an electronic data collection instrument, before and after reviewing the GC test report. Physicians also completed a Decision Conflict Scale (DCS), a decisional conflict measure, to assess their confidence with their treatment recommendations.Over 60% of high-risk patients were re-classified as low risk after review of the GC test results. Overall, adjuvant treatment recommendations were modified for 30.8% (95% CI = 23-39%) of patients. With GC test results, 42.5% of patients who were initially recommended adjuvant therapy were subsequently recommended observation. Although the number of patients recommended adjuvant therapy remained the same before and after review of the GC test results, it did influence patient treatment strategies. Multivariable analysis confirmed GC risk was the only significant predictor of treatment recommendations (OR = 4.04; 95% CI = 2.36, 6.92; p 0.0001). Decisional conflict with regard to adjuvant treatment decisions was significantly less with the use of the GC test (p 0.0001).Information on individualized metastasis risk based on a patient's tumor biology, with use of the GC test, significantly changed urologists' adjuvant treatment recommendations for post-operative patients with prostate cancer, who were at high risk of metastasis. Namely, the results of this study provide evidence for the utility of the GC test, and show it may guide use of adjuvant radiation.

Urinary continence is a driver of quality of life after radical prostatectomy. In this study we evaluated the impact of a biological bladder neck sling on the return of urinary continence after robot-assisted radical prostatectomy.This study compared early continence in patients undergoing robot-assisted radical prostatectomy with a sling and without a sling in a 2-group, 1:1, parallel, randomized controlled trial. Patients were blinded to group assignment. The primary outcome was defined as urinary continence (0 to 1 pad per day) at 1 month postoperatively. Inclusion criteria were organ confined prostate cancer and a prostate specific antigen less than 15 ng/ml. Exclusion criteria were any prior surgery on the prostate, a history of neurogenic bladder and history of pelvic radiation. A chi-squared test was used for the primary outcome.A total of 147 patients were randomized (control 74, sling 73) and 92% were available for primary end point analysis at 1 month. There were no significant differences in baseline or perioperative data except that operating room time was 20.1 minutes longer for the sling group (p=0.04). The continence rate was similar between the control and sling groups at 1 month (47.1% vs 55.2%, p=0.34) and 12 months (86.7% vs 94.5%, p=0.15), respectively. Adverse events were similar between the control and sling groups (10.8% vs 13.7%, p=0.59).The application of an absorbable urethral sling at robot-assisted radical prostatectomy was well tolerated with no increase in obstructive symptoms in this randomized trial. However, the sling failed to show a significant improvement in continence.

The cell cycle progression test is a validated molecular assay that assesses prostate cancer specific disease progression and mortality risk when combined with clinicopathological parameters. We present the results from PROCEDE-1000, a large, prospective registry designed to evaluate the impact of the cell cycle progression test on shared treatment decision making for patients newly diagnosed with prostate cancer.Untreated patients with newly diagnosed prostate adenocarcinoma were enrolled in the study and the cell cycle progression test was performed on the initial prostate biopsy tissue. A set of 4 sequential surveys tracked changes relative to initial therapy recommendations (before cell cycle progression) based on clinicopathological parameters following physician review of the cell cycle progression test result, physician/patient review of the cell cycle progression test results and a minimum of 3 months of clinical followup (actual treatment).Of the 1,596 patients enrolled in this registry 1,206 were eligible for analysis. There was a significant reduction in the treatment burden recorded at each successive evaluation (p0.0001), with the mean number of treatments per patient decreasing from 1.72 before the cell cycle progression test to 1.16 in actual followup. The cell cycle progression test caused a change in actual treatment in 47.8% of patients. Of these changes 72.1% were reductions and 26.9% were increases in treatment. For each clinical risk category there was a significant change in treatment modality (intervention vs nonintervention) before vs after cell cycle progression testing (p=0.0002).The cell cycle progression test has a significant impact in assisting physicians and patients reach personalized treatment decisions.

Objectives To evaluate the impact of a genomic classifier (GC) test for predicting metastasis risk after radical prostatectomy (RP) on urologists' decision-making about adjuvant treatment of patients with high-risk prostate cancer. Subjects and Methods Patient case history was extracted from the medical records of each of the 145 patients with pT3 disease or positive surgical margins (PSMs) after RP treated by six high-volume urologists, from five community practices. GC results were available for 122 (84%) of these patients. US board-certified urologists (n = 107) were invited to provide adjuvant treatment recommendations for 10 cases randomly drawn from the pool of patient case histories. For each case, the study participants were asked to make an adjuvant therapy recommendation without (clinical variables only) and with knowledge of the GC test results. Recommendations were made without knowledge of other participants' responses and the presentation of case histories was randomised to minimise recall bias. Results A total of 110 patient case histories were available for review by the study participants. The median patient age was 62 years, 71% of patients had pT3 disease and 63% had PSMs. The median (range) 5-year predicted probability of metastasis by the GC test for the cohort was 3.9 (1–33)% and the GC test classified 72% of patients as having low risk for metastasis. A total of 51 urologists consented to the study and provided 530 adjuvant treatment recommendations without, and 530 with knowledge of the GC test results. Study participants performed a mean of 130 RPs/year and 55% were from community-based practices. Without GC test result knowledge, observation was recommended for 57% (n = 303), adjuvant radiation therapy (ART) for 36% (n = 193) and other treatments for 7% (n = 34) of patients. Overall, 31% (95% CI: 27–35%) of treatment recommendations changed with knowledge of the GC test results. Of the ART recommendations without GC test result knowledge, 40% (n = 77) changed to observation (95% CI: 33–47%) with this knowledge. Of patients recommended for observation, 13% (n = 38 [95% CI: 9–17%]) were changed to ART with knowledge of the GC test result. Patients with low risk disease according to the GC test were recommended for observation 81% of the time (n = 276), while of those with high risk, 65% were recommended for treatment (n = 118; P < 0.001). Treatment intensity was strongly correlated with the GC-predicted probability of metastasis (P < 0.001) and the GC test was the dominant risk factor driving decisions in multivariable analysis (odds ratio 8.6, 95% CI: 5.3–14.3%; P < 0.001). Conclusions Knowledge of GC test results had a direct effect on treatment strategies after surgery. Recommendations for observation increased by 20% for patients assessed by the GC test to be at low risk of metastasis, whereas recommendations for treatment increased by 16% for patients at high risk of metastasis. These results suggest that the implementation of genomic testing in clinical practice may lead to significant changes in adjuvant therapy decision-making for high-risk prostate cancer.

We determine the impact of a single dose of a diuretic given to patients scheduled for flow rate recording on clinic waiting time and flow rate parameters, and whether such practice induces artifacts in recording independent of those inherent in repeat recordings.A total of 99 volunteers with a mean age plus or minus standard deviation of 54 +/- 10.9 years with no known urological condition participated in an open label, crossover study. On 2 separate occasions they came to the clinic for a flow rate recording, and were randomized to receive 20 mg. furosemide upon arrival at the first or second visit. Clinic waiting time, pre-void bladder volume, voided volume, maximum flow rate and other parameters were captured in a database and analyzed.Independent of diuretic use an increase in voided volume and maximum flow rate (19.8 to 21.2 ml. per second) was noted from the first to second visit. Diuretic use independent of sequence induced an increase in voided volume and significant reduction in waiting time (155 versus 81 minutes, p0.001) without affecting maximum flow rate (19.9 versus 21.1 ml. per second, p = 0.058). Diuretic use on the second visit enhanced the learning effect on maximum flow rate, while first visit use negated the learning effect on the second visit. Waiting time reduction was significant independent of sequence. The positive correlation between voided volume and maximum flow rate remained unchanged with or without the diuretic.Repeat flow rate recordings are associated with a measurable learning effect leading to an increase in maximum flow rate. The use of 20 mg. furosemide reduces waiting time without inducing additional artifacts or significant changes in flow rate parameters. This practice is recommended for busy offices or clinical research centers to enhance urine flow, patient satisfaction and ultimately compliance with care.

e16567Background: A novel tissue based biomarker panel is developed to objectively assess disease aggressiveness and invasive potential of Prostate Cancer (CaP). The biomarker diagnostic platform i...

338 Background: A novel tissue based biomarker panel is introduced to objectively assess disease aggressiveness and invasive potential of Prostate Cancer (CaP). The biomarker diagnostic platform incorporates both molecular and phenotypic data that may allow an improved understanding of local growth and metastatic potential. The tissue based diagnostic incorporates matrix biology, phenotypic biomarkers, microfluidics, and machine vision. This technology presents the opportunity to culture samples, and both determine and automate biomarker measurements from machine vision algorithm analysis. Data are presented towards clinical validation, the ability to risk stratify, and prediction of local aggressiveness and metastasis. Methods: Conditions were optimized for reliably culturing primary cancer cells in vitro by simulating in vivo conditions on an extracellular matrix formulation. A mcirofluidics device was used to culture live tumor samples ex vivo enabling automated imaging of the label free and label-based biomarkers. Results: The validation study was IRB approved and performed in 200 consecutive CaP radical prostatectomy derived specimens collected between 03/2014 and 09/2015. Data was analyzed with receiver operating characteristics (ROC) generated Area-under-the-Curve (AUC) and specifically included capsular penetration, seminal vesicle invasion, as well as margin-positive disease. AUC Graphs are presented. The study further demonstrated that a normal set of phenotypic biomarkers can produce secondary metrics termed oncogenic potential (OP) and metastatic potential (MP). Concordance analysis supports that OP and MP are integral for distinguishing between benign histology and malignancy, predicting both stage and adverse pathology such as extra-prostatic extension (EPE) and lympho-vascular invasion (LVI). The study results demonstrate AUCs greater than 0.90 in predicting EPE and LVI. Conclusions: Results support the clinical validation of a novel live- cell phenotypic in vitro tumor diagnostic test. This test has the potential to predict adverse pathologies for CaP and may have extended clinical applications to optimize staging and risk stratification.

We present a unique case of incidentally discovered symptomatic, stone-laden ureteroceles after robotic prostatectomy at a high-volume institution. The 2-month postoperative timeline to presentation and laser unroofing management strategy for bilateral ureteroceles after robotic prostatectomy are described.

Due to the inconsistencies of existing molecular, genomic, and pathophysiologic markers for patient risk stratification, effective prostate cancer diagnostics and treatment remains a challenge in clinical practice. Therefore, the development of a diagnostic platform that differentiates cancer patients who have clinically significant disease from those who have a low risk of progression is an important area of interest. In this study, we tested a diagnostic platform that combines a scalable microfluidic device, an automated live cell assay, and objective machine vision algorithms to measure phenotypic biomarkers [defined here as functional biophysical and molecular biomarkers], which evaluate both local growth and metastatic potential of prostate cancer. An analytical validation study was performed on fresh prostate cancer samples (n = 100) obtained at the time of radical prostatectomy (RP). The diagnostic platform enables: 1) growth of patient cells ex vivo on extra cellular matrix formulations supporting adhesion/survival for 72 hours 2) high-throughput imaging of multiple phenotypic biomarkers such as morphology, cytoskeleton dynamics, and protein subcellular localization & modification states and 3) objective quantification of biomarkers via machine vision analysis. Patient samples were imaged over a three hour period capturing live-cell biophysical biomarkers. After three hours cells were fixed and stained for molecular biomarkers. Machine vision technology was then utilized to analyze phenotypic biomarkers to yield specific metrics that quantified local tumor growth (Oncogenic Potential-OPs) and invasive potential of the tumor to other tissues (Metastatic Potential- MPs) that correlated with RP specimen pathologic findings. Analysis of quantified phenotypic biomarkers distinguished normal cells from cancer cells. The OP and MP metrics demonstrated statistical significance in distinguishing Gleason 6 (low-risk) from Gleason 7 (intermediate-risk) prostate cancer with 80% sensitivity and 80% specificity and concordance with relevant RP pathology findings. Specifically, OP and MP derived from defined phenotypic biomarker metrics, demonstrated the ability to differentiate Gleason 6 and 7 scores and correlated with, 1) seminal vesicle invasion, 2) positive RP surgical margins, 3) vascular invasion, and 4) lymph node involvement. This novel functional-live-cell diagnostic platform allows for the measurement of a biomarker panel that further stratifies patients to improve prostate cancer treatment, clinical decision-making, further risk stratification of intermediate prostate cancer populations, and potentially predict actionable pathological findings leading to improved treatment outcomes for prostate cancer patients. Citation Format: Michael S. Manak, Wendell R. Su, Andrew Min, Brad J. Hogan, Matthew J. Whitfield, Jonathan S. Varsanik, Delaney Berger, Mani Foroohar, Kimberly M. Rieger-Christ, Travis B. Sullivan, Naveen Kella, Ray Hernandez, Vladimir Mouraviev, Kevin B. Knopf, Hani H. Rashid, David M. Albala, Grannum R. Sant, Ashok C. Chander. A novel live cell diagnostic platform measuring phenotypic biomarkers using objective algorithmic analysis enables further risk stratification for intermediate-risk prostate cancer patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4347. doi:10.1158/1538-7445.AM2015-4347

e16031 Background: Overdiagnosis and overtreatment of prostate cancer is a problem that requires the need for a diagnostic test that can predict cancer aggressiveness and metastatic potential. Cell...

211 Background: Over-treatment of prostate cancer affects 144,000 patients annually in the U.S. due to the inaccuracy of current diagnostics for risk stratification. Functional molecular and biophysical biomarkers combined with clinically actionable diagnostic platforms are used for evaluating the local invasiveness and metastatic potential of cells derived from biopsy. Such a diagnostic test may improve patient outcomes in low-to high-risk prostate cancers according to D’Amico’s definition. This study describes the development of a novel phenotypic diagnostic using a set of biomarkers measured with a proprietary live cell assay coupled with innovative machine vision algorithms for patient tumor samples using a unique microfluidic platform. Methods: We assessed 60 prostate cancer samples collected post radical prostatectomy (RP). We report the assay details for culturing live tumor cells ex vivo, enabling automated imaging of phenotypic biomarkers. The test is designed to sustain survival of prostate tumor cells from fresh biopsy/surgical samples for up to three days prior to analysis of phenotypic characteristics. Results: We show that this test distinguishes live normal and tumor cells via molecular and biophysical biomarkers. The primary biomarkers are calculated using objective machine vision algorithms and are used to derive secondary metrics termed “Metastatic Potential (MP) and Oncogenic Potential (OP)”. In comparing clinical measures with results of this test, concordance analysis show that OP and MP are statistically significant in distinguishing between Gleason 6 and Gleason 7 with 85% sensitivity and 80% specificity. Conclusions: This phenotypic diagnostic generates scoring metrics of MP and OP that correlate with 1) aggressive vs. indolent Gleason 6, 2) seminal vesicle invasion, 3) occurrence of margins after RP, 4) lymph node invasion and 5) systemic metastatic process. These results will further help stratify patient tumors to improve clinical decision-making in low to intermediate- and high-risk prostate cancer populations, and potentially avoid unnecessary surgery or radiation, ultimately leading to improved patient quality of life.

63 Background: The cell cycle progression (CCP) test is a validated molecular assay that assesses risk of prostate cancer−specific disease progression and mortality when combined with standard clinicopathologic parameters. PROCEDE−1000 is the largest prospective registry to evaluate CCP test impact on personalizing prostate cancer treatment. Results of an interim analysis are presented. Methods: Untreated patients with newly diagnosed (≤6 months), clinically localized prostate adenocarcinoma were enrolled (n=816). The physician’s initial therapy recommendation (pre−CCP) was recorded on the first questionnaire. The CCP test was then conducted on prostate biopsy tissue. Three post−CCP questionnaires recorded the physician’s revised treatment recommendation, physician/patient treatment decision, and actual treatment administered. Changes in treatments between the pre-CCP and post−CCP questionnaires demonstrated the impact of CCP testing on treatment decisions at each stage. Results: Visual analog scale measurements indicated a significant increase (p=0.0125) in the physician’s likelihood of recommending non−interventional treatment post−CCP test; there was an increase in active surveillance from the initial interventional therapy recommendation. From pre−CCP therapy recommendation, the CCP score caused a change in actual treatment administered in 44% of patients; 72% of changes were reductions in treatment. Reductions occurred in radical prostatectomy (27%), radiation therapy (44% primary; 56% adjuvant), brachytherapy (46% interstitial; 66% HDR) and hormonal therapy (33% neoadjuvant; 68% concurrent) treatments. While 35.9% of patients were recommended for conservative management pre−CCP testing, there was a 6.5% increase in non−interventional treatments during actual follow−up. Overall, there was a significant reduction in the number of treatment options at each successive evaluation (p