Predictor Of Adverse Pathology Research Articles

Radiographic predictors of muscle-invasive upper tract urothelial cancer

Introduction: Accurate diagnostic staging of upper tract urothelial cancer (UTUC) is challenging. Endoscopic staging is limited by its ability to provide adequate sampling of deeper layers of the ureter and renal pelvis. Further ability to accurately predict invasive disease would aid in better selecting the appropriate treatment for patients. We aimed to analyze the ability of preoperative cross-sectional radiologic findings to predict pathologic outcomes, including tumor grade, muscle-invasive disease, and presence of lymphovascular invasion (LVI). Methods: All patients diagnosed with localized UTUC (cN0M0) who underwent nephroureterectomy between February 2012 and December 2018 in Manitoba, Canada, were identified. Preoperative radiologic characteristics, including the presence and severity of hydronephrosis, as well as tumor location were recorded. Patients’ and pathologic characteristics were also recorded. Logistic regression analysis was used to assess the association between radiologic variables and pathologic outcomes at radical surgery. Results: A total of 112 pathology reports of patients with UTUC were obtained. The median age was 70 years (range 50–87), and 58.8% of patients were men. On univariate analysis, ureteric location on computed tomography (odds ratio [OR] 2.240, 95% confidence interval [CU] 1.049–4.783, p=0.037) and presence of hydronephrosis (OR 2.455, 95% CI 1.094–5.506, p=0.0029) were each independently associated with locally invasive disease (>pT2). No radiologic variables were found to be a predictor of adverse pathology on multivariable analysis. Only the presence of hydronephrosis was associated with high-grade disease on univariate analysis (OR 2.533, 95% CI 1.083–5.931, p=0.032). Conclusions: Our findings suggest a limited role for cross-sectional imaging in predicting the presence of high-grade disease, LVI, or locally advanced disease in UTUC.

Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography-Derived Radiomic Models in Prostate Cancer Prognostication.

The clinical integration of prostate membrane specific antigen (PSMA) positron emission tomography and computed tomography (PET/CT) scans represents potential for advanced data analysis techniques in prostate cancer (PC) prognostication. Among these tools is the use of radiomics, a computer-based method of extracting and quantitatively analyzing subvisual features in medical imaging. Within this context, the present review seeks to summarize the current literature on the use of PSMA PET/CT-derived radiomics in PC risk stratification. A stepwise literature search of publications from 2017 to 2023 was performed. Of 23 articles on PSMA PET/CT-derived prostate radiomics, PC diagnosis, prediction of biopsy Gleason score (GS), prediction of adverse pathology, and treatment outcomes were the primary endpoints of 4 (17.4%), 5 (21.7%), 7 (30.4%), and 7 (30.4%) studies, respectively. In predicting PC diagnosis, PSMA PET/CT-derived models performed well, with receiver operator characteristic curve area under the curve (ROC-AUC) values of 0.85-0.925. Similarly, in the prediction of biopsy and surgical pathology results, ROC-AUC values had ranges of 0.719-0.84 and 0.84-0.95, respectively. Finally, prediction of recurrence, progression, or survival following treatment was explored in nine studies, with ROC-AUC ranging 0.698-0.90. Of the 23 studies included in this review, 2 (8.7%) included external validation. While explorations of PSMA PET/CT-derived radiomic models are immature in follow-up and experience, these results represent great potential for future investigation and exploration. Prior to consideration for clinical use, however, rigorous validation in feature reproducibility and biologic validation of radiomic signatures must be prioritized.

The Role of Multiparametric MRI (mpMRI) in the Prediction of Adverse Prostate Cancer Pathology in Radical Prostatectomy Specimen.

Prostate cancer (PCa) risk stratification is essential in guiding therapeutic decision. Multiparametric magnetic resonance tomography (mpMRI) holds promise in the prediction of adverse pathologies (AP) after prostatectomy (RP). This study aims to identify clinical and imaging markers in the prediction of adverse pathology. Patients with PCa, diagnosed by targeted biopsy after mpMRI and undergoing RP, were included. The predictive accuracy of mpMRI for extraprostatic extension (ECE), seminal vesicle infiltration (SVI), and lymph node positivity was calculated from the final histopathology. 846 patients were involved. Independent risk parameters include imaging findings such as ECE (OR 3.12), SVI (OR 2.55), and PI-RADS scoring (4: OR 2.01 and 5: OR 4.34). mpMRI parameters such as ECE, SVI, and lymph node metastases showed a high prognostic accuracy (73.28% vs. 95.35% vs. 93.38%) with moderate sensitivity compared to the final histopathology. The ROC analysis of our combined scoring system (D'Amico classification, PSA density, and MRI risk factors) improves the prediction of adverse pathology (AUC: 0.73 vs. 0.69). Our study supports the use of mpMRI for comprehensive pretreatment risk assessment in PCa. Due to the high accuracy of factors like ECE, SVI, and PI-RADS scoring, utilizing mpMRI data enabled accurate prediction of unfavorable pathology after RP.

Large cribriform glands (> 0.25 mm diameter) as a predictor of adverse pathology in men with Grade Group 2 prostate cancer.

A recent outcome-based, radical prostatectomy study defined > 0.25 mm diameter to distinguish large versus small cribriform glands, with > 0.25 mm associated with worse recurrence-free survival. This study evaluates whether identification of > 0.25 mm cribriform glands in Grade Group 2 patients at biopsy is associated with adverse pathology at radical prostatectomy. Tumours containing biopsy slides for 133 patients with Grade Group 2 prostate cancer with subsequent radical prostatectomy were re-reviewed for large cribriform glands (diameter > 0.25 mm). The primary outcome was adverse pathology (Grade Groups 3-5; stage pT3a or greater, or pN1). The secondary outcome was recurrence-free survival. Cribriform pattern was present in 52 of 133 (39%) patients; of these, 16 of 52 (31%) had large cribriform glands and 36 of 52 (69%) had only small cribriform glands. Patients with large cribriform glands had significantly more adverse pathology at radical prostatectomy compared to patients with small cribriform glands and no cribriform glands (large = 11 of 16, 69%; small = 12 of 36, 33%; no cribriform = 25 of 81, 31%; χ2 P-value 0.01). On multivariate analysis, large cribriform glands were also associated with adverse pathology, independent of age, prostate-specific antigen (PSA)/PSA density at diagnosis, year of diagnosis and biopsy cores percentage positive (global P-value 0.02). Large cribriform glands were also associated with increased CAPRA-S surgical risk score (Kruskal-Wallis P-value 0.02). Large cribriform glands using a diameter > 0.25 mm definition in Grade Group 2 patients on biopsy are associated with increased risk of adverse pathology at radical prostatectomy. The presence of large cribriform histology should be considered when offering active surveillance for those with Grade Group 2 disease.

Predictor of adverse pathology in patients who underwent deferred radical prostatectomy following active surveillance: Results from multi-institutional prospective observational cohort in the PRIAS-JAPAN.

350 Background: Intraductal carcinoma of the prostate (IDC-P) and invasive cribriform are key prognostic pathologies among early stage prostate cancer patients; however, predictors of adverse pathology, including these types, remain unknown. In men who opted for active surveillance (AS), we aimed to examine the association between adverse pathology and patient characteristics, utilizing radical prostatectomy (RP) specimens. Methods: We re-reviewed available RP specimens from 1035 men prospectively enrolled in the PRIAS-JAPAN cohort between January 2010 and September 2020. We defined adverse pathology on RP specimen as Gleason grade group of ≥3, pT-stage≥T3, pN positivity, or the presence of IDC-P or invasive cribriform. And, we examined the predictive factors associated with adverse pathology, using factors at AS enrollment and before RP. Results: Out of 162 men underwent RP, available 137 RP specimens were analyzed. The percentage of adverse pathology was 48.9% (67 patients), including 8.8% in IDC-P and 29.9 % in invasive cribriform. Men with adverse pathology had lower prostate specific antigen recurrence-free survival than those without them (log rank P = 0.0189). On multivariate logistic regression analyses, increasing age at AS enrollment and before RP were the predictive factors for adverse pathology (Odds ratio [OR], 1.1; 95% confidence interval [CI]: 1.02-1.19, P = 0.0178, OR, 1.12; 95% CI: 1.02-1.22, P=0.0126), not magnetic resonance imaging findings. Conclusions: Aging is significantly associated with adverse pathology including IDC-P or cribriform. The results suggest that relaxing scheduled examinations during AS depending on age is not practical. Clinical trial information: UMIN000048095 .

Risk and predictors of adverse pathology after radical prostatectomy in patients diagnosed with IUSP 1–2 prostate cancer at MRI-targeted biopsy: a multicenter analysis

PurposeAlthough active surveillance (AS) is recommended for low- to favorable intermediate-risk prostate cancer (PCa), risk of upgrading at radical prostatectomy (RP) is not negligible. Available studies based on systematic transrectal ultrasound biopsy might not be applicable to contemporary cohorts diagnosed with MRI-targeted biopsy (TB). The aim of the present study is to explore rates and risk factors for adverse outcomes (AO) at RP in patients with ISUP ≤ 2 PCa detected at TB with concomitant systematic biopsy (SB).MethodsMulticenter, retrospective analysis of 475 consecutive patients with ISUP ≤ 2 PCa at MRI-TB + SB is treated with RP. AO were defined as ISUP upgrading, adverse pathology (upgrading to ISUP ≥ 3 and/or ≥ pT3 at RP, and/or pN1) (AP) or biochemical recurrence (BCR) in men with follow-up (n = 327).ResultsThe rate of ISUP upgrading, upgrading ≥ 3, and AP were 39%, 21%, and 43%. Compared to ISUP2, men with ISUP1 PCa had a higher rate of overall upgrading (27 vs. 67%, p < 0.001), but less upgrading to ≥ 3 (27 vs. 10%, p < 0.001). AP was more common when ISUP2 was detected with a combined MRI-TB + SB approach compared to considering TB (p = 0.02) or SB (p = 0.01) alone. PSA, PSA density, PI-RADS, ISUP at TB, overall biopsy ISUP and EAU classification were predictors of upgrading to ISUP ≥ 3 and AP. The 1 year BCR-free survival was 94% with no differences in BCR rates between subgroups.ConclusionUpgrading in ISUP ≤ 2 PCa remains prevalent even in men diagnosed in the MRI era. The use of MRI-TB with concomitant SB allows for the accurate identification of ISUP2 PCa and predicts the risk of AO at RP.

Prediction of Adverse Pathology at Radical Prostatectomy in Grade Group 2 and 3 Prostate Biopsies Using Machine Learning.

There is ongoing clinical need to improve estimates of disease outcome in prostate cancer. Machine learning (ML) approaches to pathologic diagnosis and prognosis are a promising and increasingly used strategy. In this study, we use an ML algorithm for prediction of adverse outcomes at radical prostatectomy (RP) using whole-slide images (WSIs) of prostate biopsies with Grade Group (GG) 2 or 3 disease. We performed a retrospective review of prostate biopsies collected at our institution which had corresponding RP, GG 2 or 3 disease one or more cores, and no biopsies with higher than GG 3 disease. A hematoxylin and eosin-stained core needle biopsy from each site with GG 2 or 3 disease was scanned and used as the sole input for the algorithm. The ML pipeline had three phases: image preprocessing, feature extraction, and adverse outcome prediction. First, patches were extracted from each biopsy scan. Subsequently, the pre-trained Visual Geometry Group-16 convolutional neural network was used for feature extraction. A representative feature vector was then used as input to an Extreme Gradient Boosting classifier for predicting the binary adverse outcome. We subsequently assessed patient clinical risk using CAPRA score for comparison with the ML pipeline results. The data set included 361 WSIs from 107 patients (56 with adverse pathology at RP). The area under the receiver operating characteristic curves for the ML classification were 0.72 (95% CI, 0.62 to 0.81), 0.65 (95% CI, 0.53 to 0.79) and 0.89 (95% CI, 0.79 to 1.00) for the entire cohort, and GG 2 and GG 3 patients, respectively, similar to the performance of the CAPRA clinical risk assessment. We provide evidence for the potential of ML algorithms to use WSIs of needle core prostate biopsies to estimate clinically relevant prostate cancer outcomes.

Prostate MRI percentage tumor involvement or "PI-RADS percent" as a predictor of adverse surgical pathology.

This study assesses magnetic resonance imaging (MRI) prostate % tumor involvement or "PI-RADs percent" as a predictor of adverse pathology (AP) after surgery for localized prostate cancer (PCa). Two separate variables, "All PI-RADS percent" (APP) and "Highest PI-RADS percent" (HPP), are defined as the volume of All PI-RADS 3-5 score lesions on MRI and the volume of the Highest PI-RADS 3-5 score lesion each divided by TPV, respectively. An analysis was done of an IRB approved prospective cohort of 557 patients with localized PCa who had targeted biopsy of MRI PIRADs 3-5 lesions followed by RARP from April 2015 to May 2020 performed by a single surgeon at a single center. AP was defined as ISUP GGG ≥3, pT stage ≥T3 and/or LNI. Univariate and multivariable analyses were used to evaluate APP and HPP at predicting AP with other clinical variables such as Age, PSA at surgery, Race, Biopsy GGG, mpMRI ECE and mpMRI SVI. Internal and External Validation demonstrated predicted probabilities versus observed probabilities. AP was reported in 44.5% (n = 248) of patients. Multivariable regression showed both APP (odds ratio [OR]: 1.10, 95% confidence interval [CI]: 1.04-1.14, p = 0.0007) and HPP (OR: 1.10; 95% CI: 1.04-1.16; p = 0.0007) were significantly associated with AP with individual area under the operating curves (AUCs) of 0.6142 and 0.6229, respectively, and AUCs of 0.8129 and 0.8124 when incorporated in models including preoperative PSA and highest biopsy GGG. Increasing PI-RADS Percent was associated with a higher risk of AP, and both APP and HPP may have clinical utility as predictors of AP in GGG 1 and 2 patients being considered for AS. Using PIRADs percent to predict AP for presurgical patients may help risk stratification, and for low and low volume intermediate risk patients, may influence treatment decisions.

Association of Age With Risk of Adverse Pathological Findings in Men Undergoing Delayed Radical Prostatectomy Following Active Surveillance

ObjectivesTo determine if older men with Gleason grade group (GG) 1 prostate cancer have a higher risk of having adverse pathology at radical prostatectomy after initially being managed with active surveillance (AS). MethodsA total of 365 patients with GG1 prostate cancer initially managed with AS followed by delayed radical prostatectomy were identified. The primary outcome was adverse pathology after delayed radical prostatectomy in the men that were <65 years vs. men ≥65 years at the initiation of AS. Adverse pathology was defined as GG ≥3 or pT3 or pN1. Multivariable Cox proportional hazards regression models were used to calculate risk of adverse pathological findings at radical prostatectomy by age group. ResultsAt diagnosis, there were no significant differences in median prostate specific antigen density, percent positive biopsy cores, multiparametric magnetic resonance imaging (mpMRI) results or composite genomic classifier scores (derived from three commercially available genomic tests) between the two age groups. Men ≥65 years had more adverse pathology at radical prostatectomy (59.2% vs. 44.1%, P <0.01) and lower rates of biopsy upgrade-free survival and adverse pathology-free survival (log-rank P <0.01). On multivariable analysis age ≥65 years (Hazard Ratio (HR) 2.21, 95% Confidence Interval (CI) 1.57, 3.12) was associated with adverse pathology at radical prostatectomy. In separate multivariable analyses done for each age group, mpMRI (HR 3.33, 95% CI 1.01, 10.95) was predictor of adverse pathology in the group ≥65 years. ConclusionOlder patients might require closer monitoring on AS and additional testing such as mpMRI might improve their risk stratification.

Predictors of adverse pathology on radical prostatectomy specimen in men initially enrolled in active surveillance for low-risk prostate cancer

PurposeTo evaluate clinical variables, including magnetic resonance imaging (MRI) predictive of adverse pathology (AP) at radical prostatectomy (RP) in men initially enrolled in active surveillance (AS).MethodsA population-based cohort study of men diagnosed with low-risk prostate cancer (PCa), in Stockholm County, Sweden, during 2008–2017 enrolled in AS their intended primary treatment followed by RP. AP was defined as ISUP grade group ≥ 3 and/or pT-stage ≥ T3. Association between clinical variables at diagnosis and time to AP was evaluated using Cox regression and multivariate logistic regression to evaluate the association between AP and clinical variables at last biopsy before RP.ResultsIn a cohort of 6021 patients with low-risk PCa, 3116 were selected for AS and 216 underwent RP. Follow-up was 10 years, with a median time on AS of 23 months. 37.7% of patients had AP at RP. Clinical T-stage [Hazard ratio (HR): 1.81, 95% confidence interval (CI) 1.04–3.18] and PSA (HR: 1.31, 95% CI 1.17–1.46) at diagnosis and age [Odds Ratio (OR): 1.09, 95% CI 1.02–1.18), PSA (OR: 1.22, 95% CI 1.07–1.41), and PI-RADS (OR 1.66, 95% CI 1.11–2.55)] at last re-biopsy were significantly associated with AP.ConclusionPI-RADS score is significantly associated with AP at RP and support current guidelines recommending MRI before enrollment in AS. Furthermore, age, cT-stage, and PSA are significantly associated with AP.

Abstract A067: Oncotype DX assay has similar predictive accuracy for adverse pathology at radical prostatectomy in African American and European American men

Abstract Objective: To validate the 17-gene Oncotype DX Genomic Prostate Score (GPS) biopsy-based gene expression assay as a predictor of adverse pathology (AP: Pathologic Gleason score ≥4+3, presence of any Gleason 5, and/or ≥pT3) in African American (AA) men. Methods: Between February 2009 and September 2014, AA and European American (EA) men with very low, low, and intermediate risk prostate cancer (PCa) enrolled in a multi-institutional prospective study of vitamin D impacts of biopsy outcomes. The subset who proceeded to immediate radical prostatectomy (RP) after biopsy with available biopsy tumor blocks was included in a comparative effectiveness analysis of GPS on biopsy and its association with surgical AP on RP using logistic regression and receiver operating characteristic curves. Multiplicative interactions tested for differential prediction of GPS accuracy by race (AA vs. EA). Results: Overall, 102 AA and 76 EA men elected RP, out of which 51 (47.2%) had AP. GPS result was a significant predictor of AP (odds ratio per 20 GPS units [OR/20 units] in AA: 4.78; 95% CI 1.8-12.5, P =0.001; and EA: 4.41; 95% CI 1.6-11.9, P =0.003) in univariable analysis. On multivariate analysis, there was a significant interaction between GPS and race (P=0.01). On race stratified binary logistic regression, AP remained significant after adjustment for NCCN risk group in both AA and EA men (OR/20 units in AA: 3.29; 95% CI 1.2-9.1, P =0.02; and EA: 4.24; 95% CI 1.4-12.6, P =0.01). Area under the curves for AP using GPS/20 units was 0.719 for AAs vs. 0.745 for EAs (P=0.39). Conclusion: In this AA validation study, the Oncotype Dx PCa assay was confirmed as an independent predictor of AP at prostatectomy in AA and EA men with similar predictive accuracy, though there was evidence of effect modification by race. Citation Format: Samuel Carbunaru, Virgilia Marcias, Peter Gann, Roohollah Sharifi, Ximing Yang, Michael Dixon, Chase Gorbein, Borko Jovanovic, Andre Kajdacsy-Balla, Adam B. Murphy. Oncotype DX assay has similar predictive accuracy for adverse pathology at radical prostatectomy in African American and European American men [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A067.

Abstract A082: ENACT: A randomized trial assessing the impact of the Oncotype DX Prostate Cancer Assay on treatment decision in a racially diverse population of men eligible for active surveillance

Abstract The Oncotype DX Prostate Cancer Assay® (ODX), a 17-gene expression profile performed on biopsy tissue, has been validated for prediction of adverse pathology at surgery and 10-year risk of metastasis or death. The assay output provided to the patient and clinician is a predicted probability. While these studies confirm the ability of the assay to discriminate indolent from aggressive prostate cancer (PCa), the assay’s actual clinical utility, in terms of its impact on treatment choice and psychological factors, has not been determined. Moreover, the assay’s utility for African American (AA) men remains an important knowledge gap for programs aimed at reducing PCa disparities through judicious use of active surveillance (AS). ENACT (Engaging Newly Diagnosed Men About Cancer Treatment Options) is an ongoing randomized trial comparing standard National Comprehensive Cancer Network (NCCN) based treatment counseling plus ODX to NCCN-based counseling alone for a largely AA population of men eligible for AS. The primary aim is to quantify the effect of ODX on treatment, testing the hypothesis that the assay causes a net migration towards AS. Secondary aims measure effects on psychological metrics dealing with cancer-related anxiety, decision conflict, and decision regret. Completion of the trial is expected in Fall 2019. Patients are enrolled at the UI Hospital, Stroger-Cook County Hospital and the Jesse Brown VA Medical Center in Chicago. Eligibility criteria include: biopsy-proven PCa with NCCN risk level Very Low, Low or Low Intermediate, age ⇐ 76, and estimated life expectancy &amp;gt;10 years. Thus far, 201 patients have enrolled and 180 have completed all study visits. Randomization (stratified by race and NCCN risk) occurs at Visit 1, when patients receive their diagnosis and initial counseling, and treatment decision is finalized at Visit 2, 2-3 weeks later. At Visit 3, ≈4 weeks after the decision but before treatment, surveys capture information about decision conflict and changes from Visit 1 in perceived cancer-related risk/mood. At Visit 4, ≈4 months after treatment starts, final surveys capture data on regret and evaluation of the decision process. Additional surveys record treatment preference of the attending urologist before and after the final decision. The enrolled population thus far is 71% AA, 35% age &amp;lt;60, and 42% NCCN Very Low risk, 33% Low risk, and 25% Low Intermediate risk. Drop-out for the primary endpoint is &amp;lt;5%. The data analysis will explore potential effect modification by race, risk level, health literacy, marital status, and relative vs. absolute change in predicted risk. The unique design of the ENACT trial raises questions about the need to evaluate predictive biomarkers, which are decision support tools, based on their actual impact on decision quality, especially for patients affected by a racial disparity in outcomes. The advent of multiplex biomarkers that provide clinicians and patients with probabilities rather than binary results adds to the complexity and the urgency of this need. Citation Format: Adam B Murphy, Samuel Carbunaru, Michael Abern, Courtney MP Hollowell, Roohollah Sharifi, Peter H. Gann. ENACT: A randomized trial assessing the impact of the Oncotype DX Prostate Cancer Assay on treatment decision in a racially diverse population of men eligible for active surveillance [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A082.

A 17-Gene Panel Genomic Prostate Score Has Similar Predictive Accuracy for Adverse Pathology at Radical Prostatectomy in African American and European American Men

ObjectiveTo validate the 17-gene Oncotype DX Genomic Prostate Score (GPS) as a predictor of adverse pathology (AP) in African American (AA) men and to assess the distribution of GPS in AA and European American (EA) men with localized prostate cancer. MethodsThe study populations were derived from 2 multi-institutional observational studies. Between February 2009 and September 2014, AA and EA men who elected immediate radical prostatectomy after a ≥10-core transrectal ultrasound biopsy were included in the study. Logistic regressions, area under the receiver operating characteristics curves (AUC), calibration curves, and predictive values were used to compare the accuracy of GPS. AP was defined as primary Gleason grade 4, presence of any Gleason pattern 5, and/or non-organ-confined disease (≥pT3aN0M0) at radical prostatectomy. ResultsOverall, 96 AA and 76 EA men were selected and 46 (26.7%) had AP. GPS result was a significant predictor of AP (odds ratio per 20 GPS units [OR/20 units] in AA: 4.58; 95% confidence interval (CI) 1.8-11.5, P = .001; and EA: 4.88; 95% CI 1.8-13.5, P = .002). On multivariate analysis, there was no significant interaction between GPS and race (P >.10). GPS remained significant in models adjusted for either National Comprehensive Cancer Network (NCCN) risk group or Cancer of the Prostate Risk Assessment (CAPRA) score. In race-stratified models, area under the receiver operating characteristics curves for GPS/20 units was 0.69 for AAs vs 0.74 for EAs (P = .79). The GPS distributions were not statistically different by race (all P >.05). ConclusionIn this clinical validation study, the Oncotype DX GPS is an independent predictor of AP at prostatectomy in AA and EA men with similar predictive accuracy and distributions.

Adverse pathology after radical prostatectomy: the prognostic role of cumulative cancer length >6-mm threshold in prostate cancer-positive biopsies.

BackgroundTo investigate the role of Cumulative Cancer Length (CCL) and PCa positive core number (PCapcn) in random prostate biopsies as predictors of Adverse Pathology (AP) at definitive pathology.MethodsWe prospectively enrolled patients submitted to random ultrasound guided prostate biopsies for suspect PCa in our center since 2016. Inclusion criteria were PSA <20 ng/ml or >3 ng/ml and age<71 years. Data on CCL and Grade Group (GG) at biopsy and pathology after Radical Prostatectomy (RP) were collected. AP was defined as pT3 or higher TNM, Positive Surgical Margin (>2mm) or PCa Positive Lymph Node. ROC curve was used to establish an appropriate CCL and PCapcn thresholds that were then investigated as predictors of AP at definitive pathology.ResultsAmong 882 eligible biopsies, 344 had PCa and underwent RP. Mean age was 64 years (SD 5). Mean PSA was 7.75 (SD: 3.66). At definitive pathology there were AP features in 196 (56.9%) RP. PCapcn and CCL were statistically significantly associated with AP (p<0.0001). At multivariate age-adjusted logistic regression only PCapcn had an OR of 1.513 (CI95% 1.140-2.007) p=0.004. Through ROC curve a CCL>6mm and PCapcn >3 thresholds for AP were established (Area: 0.769; p<0.0001 CI 95% 0.698-0.840 and Area: 0.767; p<0.0001 CI 95% 0.696-0.837). When considering CCL>6mm AP had OR 5.462 (CI 95% 2.717-10.978) p<0.0001 and PCapcn >3 had OR 7.127 (CI 95% 3.366-15.090) p<0.0001. In particular, for GG 1 and 2, CCL>6mm had OR 3.989 (CI 95% 1.839-8.652) p<0.0001, while PCapcn >3 had OR 5.541 (CI 95% 2.390-12.849) p<0.0001.ConclusionsAt present time, random prostate biopsies might carry useful information regarding tumor extension and aggressiveness. A CCL>6mm or PCapcn >3 might be associated with AP features, in particular for low and favorable intermediate risk PCa.

The relative contributions of the Genomic Prostate Score and comorbidity profile in predicting outcomes in surgically treated men with clinically low and intermediate-risk prostate cancer.

e16607 Background: The 17-gene Oncotype Dx Genomic Prostate Score® (GPS™) assay has been validated as a predictor of aggressive prostate cancer (PCa) in men treated with radical prostatectomy (RP) for clinically low and intermediate risk PCa. This study examined the performance of the GPS assay as a predictor of adverse pathology (AP) and biochemical recurrence (BCR)-free survival (BRFS), after adjusting for the presence of major comorbidities commonly seen in older men. Methods: Additional analyses were performed using data from a prior clinical validation study of the GPS assay. GPS values (scaled 0-100), determined from diagnostic biopsy tissue, were categorized into 3 levels: lowest quartile (Q1), middle quartiles (combined Q2-Q3) versus the highest quartile (Q4). Major comorbidities included heart disease, stroke, COPD, and other cancers. The associations between GPS result and the presence of ≥1 major comorbidity and outcomes were examined. AP was defined as high-grade (Gleason Score ≥ 4+3) and/or pT3 tumor. BCR was defined as 2 successive PSA levels &gt; 0.2 ng/mL. Logistic regression analysis was used to examine AP; Cox proportional hazards analysis was used to model BRFS. Results: Among 389 eligible men, median age at diagnosis and follow-up time was 62 and 5.6 years, respectively. The prevalence of ≥1 major comorbidity differed significantly across GPS category, rising from 10.2% to 19.7% to 25.5% for GPS Quartiles 1, 2-3, and 4, respectively (p = 0.0024). However, presence of ≥1 major comorbidity was not a significant predictor of AP or BCR in multivariable models with GPS, age, race, and NCCN risk stratum. Men whose GPS result was in the highest quartile had 4-fold higher odds of AP (OR: 4.1; 95% CI = 2.1-7.99, p &lt; 0.0001) at RP and a 3.5 times higher risk of BCR (HR = 3.49; 95% CI = 1.59-7.64, p = 0.002) compared to men in the lowest GPS quartile (Table 1). Conclusions: A high GPS result remains the strongest predictor of BCR and AP in this cohort of low and intermediate risk PCa men, after adjusting for the presence of major comorbidities. Further work will explore the relationships between specific comorbidities and metabolic syndrome, with GPS testing and PCa outcomes.

A 17-gene genomic prostate score as a predictor of adverse pathology for men on active surveillance.

97 Background: The OncotypeDX Genomic Prostate Score (GPS) test is a RNA expression assay that can be performed on needle-core biopsies from men with prostate cancer (PCa). GPS has previously been validated as a predictor of adverse pathology in men with low-risk prostate cancer who undergo primary radical prostatectomy (RP). We sought to determine whether GPS was associated with increased risk of adverse pathology for men enrolled on active surveillance (AS) who undergo delayed RP. Methods: Of 1,662 men enrolled on AS at the University of California San Francisco (UCSF) who consented for prospective data collection, we evaluated 215 men on AS with Gleason score (GS) 3+3 and GS 3+4 PCa who underwent GPS testing at diagnostic or confirmatory biopsy (ie. within 1 year). Patients had at least 6 biopsy cores sampled and ≤ 33% positive cores, stage T1 or T2 disease, PSA &lt; 20, and clinical Cancer of the Prostate Risk Assessment (CAPRA) score &lt; 6. The primary outcome was adverse pathology at delayed RP, defined as GS ≥ 4+3, stage ≥ pT3a or pN1. We performed Cox proportional hazards regression, and inverse probability censored weights (IPCW) models to evaluate association between GPS and adverse pathology, adjusting for CAPRA score. Results: 72 percent (N=154) of the cohort had GS 3+3, and 28 percent (N=61) had GS 3+4. 83 percent of men (N=179) were low risk, and 17 percent of men (N=36) were intermediate risk by CAPRA scoring. Median GPS was 26.4 (interquartile range [IQR]: 18.8, 34.6). Median time from diagnosis to RP was 23 months (IQR: 15, 40). 121 men had adverse pathology on delayed RP at a median time of 27 months (IQR 16, 43) to prostatectomy. In a Cox-proportional hazards regression adjusted for CAPRA, GPS was associated with increased risk of adverse pathology at delayed RP (Hazard Ratio [HR] per 5 units: 1.12, 95 Confidence Interval [CI]: 1.05, 1.20, p &lt; 0.01). CAPRA score was not associated with adverse pathology (p=0.09). IPCW model findings were very similar to Cox results. Conclusions: In patients who undergo RP after a relatively short period of AS, a higher GPS is associated with increased risk for adverse pathology on delayed RP.

A 17-gene Panel for Prediction of Adverse Prostate Cancer Pathologic Features: Prospective Clinical Validation and Utility

To validate the 17-gene Oncotype DX Genomic Prostate Score (GPS) biopsy-based gene expression assay as a predictor of adverse pathology (AP, Gleason score [pGS] ≥4+3and/or ≥pT3) in a prospectively enrolled cohort. Between July 2014 and September 2015, 1200 men with very low-, low-, and favorable intermediate-risk prostate cancer enrolled in a multi-institutional prospective study of the GPS assay (NCT03502213). The subset who proceeded to immediate radical prostatectomy (RP) after GPS testing was included in a prespecified subanalysis of GPS on biopsy and its association with surgical AP on RP using logistic regression and receiver operating characteristic curves. The effect of GPS testing on physicians' and patients' attitudes about decision making was assessed with the Decisional Conflict Scale. One hundred fourteen patients (treated by 59 physicians from 19 sites) elected RP and 40 (35%) had AP. GPS result was a significant predictor of AP (odds ratio per 20 GPS units [OR/20 units]: 2.2; 95% CI 1.2-4.1; P = .008) in univariable analysis and remained significant after adjustment for biopsy Gleason score, clinical T-stage, and logPSA (OR/20 units: 1.9; 95% CI 1.0-3.8; P = .04), or NCCN risk group (OR/20 units: 2.0; 95% CI 1.1-3.7; P = .02). Mean pre-GPS Decisional Conflict Scale score was 27 (95% CI 24-31), which improved significantly after GPS testing to 14 (95% CI 11-17) (P < .001). In this real-world multi-institutional study, the GPS assay was prospectively confirmed as an independent predictor of AP at surgery. GPS testing was associated with reduced patient decisional conflict.

Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance

AbstactBackgroundMany men diagnosed with prostate cancer are active surveillance (AS) candidates. However, AS may be associated with increased risk of disease progression and metastasis due to delayed therapy. Genomic classifiers, e.g., Decipher, may allow better risk-stratify newly diagnosed prostate cancers for AS.MethodsDecipher was initially assessed in a prospective cohort of prostatectomies to explore the correlation with clinically meaningful biologic characteristics and then assessed in diagnostic biopsies from a retrospective multicenter cohort of 266 men with National Comprehensive Cancer Network (NCCN) very low/low and favorable-intermediate risk prostate cancer. Decipher and Cancer of the Prostate Risk Assessment (CAPRA) were compared as predictors of adverse pathology (AP) for which there is universal agreement that patients with long life-expectancy are not suitable candidates for AS (primary pattern 4 or 5, advanced local stage [pT3b or greater] or lymph node involvement).ResultsDecipher from prostatectomies was significantly associated with adverse pathologic features (p-values < 0.001). Decipher from the 266 diagnostic biopsies (64.7% NCCN-very-low/low and 35.3% favorable-intermediate) was an independent predictor of AP (odds ratio 1.29 per 10% increase, 95% confidence interval [CI] 1.03–1.61, p-value 0.025) when adjusting for CAPRA. CAPRA area under curve (AUC) was 0.57, (95% CI 0.47–0.68). Adding Decipher to CAPRA increased the AUC to 0.65 (95% CI 0.58–0.70). NPV, which determines the degree of confidence in the absence of AP for patients, was 91% (95% CI 87–94%) and 96% (95% CI 90–99%) for Decipher thresholds of 0.45 and 0.2, respectively. Using a threshold of 0.2, Decipher was a significant predictor of AP when adjusting for CAPRA (p-value 0.016).ConclusionDecipher can be applied to prostate biopsies from NCCN-very-low/low and favorable-intermediate risk patients to predict absence of adverse pathologic features. These patients are predicted to be good candidates for active surveillance.

Prediction of adverse pathology after radical prostatectomy on MPMRI in the PIRADS v2 era.

121 Background: As the use of MRI in the diagnosis of prostate cancer (PCa) becomes more established, knowledge of its utility as a prognostic tool is needed to better counsel patients. Here, we aim to assess the ability of mpMRI to predict adverse pathologic factors, such as extraprostatic extension (EPE), seminal vesicle invasion (SVI) or lymph node involvement (LNI) on final pathology after radical prostatectomy (RP). Methods: A prospectively maintained database was queried for all men who underwent mpMRI with current PI-RADS v2 scoring system, MRI/TRUS fusion biopsy (FBx), and RP at our institution (n = 112). Patient demographics, clinical data, imaging and pathology were recorded. Patients were stratified by presence of adverse pathology (AP), defined as EPE, SVI or LNI. Statistical analyses were used to identify mpMRI characteristics predictive of AP using STATA 13. Results: Patients with adverse pathology were middle aged, predominantly caucasian, and significantly higher PSA at baseline (Table 1). Having a PI-RADS 5 lesion was positively associated with AP (adjusted OR = 4.37, 95% CI = 1.20-15.87, p = 0.02). Mean lesion diameter on mpMRI was greater in patients with AP (p &lt; 0.01). However, number of lesions (p = 0.12) and prostate volume on mpMRI (p = 0.88) were not associated with AP. Conclusions: The results of this study demonstrate that features on mpMRI, particularly a PI-RADS score of 5 and large lesion diameter, are predictive of adverse pathology. This information will prove valuable in developing an imaging-based prognostic model in the era of MRI and FBx. This research was supported by the Intramural Research Program of the National Cancer Institute, NIH and NIH Medical Research Scholars Program[Table: see text]

A 17-gene panel for prediction of adverse surgical pathology in the setting of MRI-guided prostate biopsy.

5063 Background: A 17 gene panel (Oncotype Dx Genomic Prostate Score, GPS) has been validated as an independent predictor of adverse pathology (AP, defined as pathological GS 4+3 or higher and/or pT3+) in men treated with radical prostatectomy (RP) for prostate cancer (PCa). Multiparametric Magnetic Resonance Imaging (mpMRI) may help guide prostate biopsies. We explored synergies between GPS and mpMRI to aid in PCa management decisions. Methods: A cohort of men with NCCN Low and Intermediate-Risk PCa who were managed with RP was identified from a clinical database. Patients were required to have had a simultaneous mpMRI-guided and systematic biopsy and to have undergone RP within 6 months. Biopsy tissue of the highest Gleason pattern was used for calculation of GPS. The primary endpoint was AP. Secondary endpoints included the range of GPS within UCLA prostate MRI risk groups and median GPS when there was discrepancy between MRI and systematic biopsy Gleason Score (GS). Logistic regression models were fit to evaluate the relationship between GPS (per 20 units) and AP. Results: 134 men met criteria for the primary endpoint. Median age was 62 years (range 46-77). NCCN Low &amp; Intermediate-Risk PCa was present in 16%, and 84% of men, respectively. Biopsy GS 3+3/3+4/4+3 was present in 19%, 67%, and 13%, respectively. In a univariable model, GPS was associated with AP (OR 3.8, 95% CI 2.1 to 7.4, p &lt; 0.001). After adjustment for highest biopsy GS and clinical T-stage, GPS remained significantly associated with AP (OR 3.4, 95% CI 1.8 to 6.8, p = 0.0004). A wide and overlapping distribution of GPS was noted across UCLA MRI prostate risk groups, indicating that GPS provides information that is distinct from what can be determined from mpMRI. When there was a discrepancy between mpMRI and systematic biopsy GS, mpMRI targeted lesions with higher GS had higher median GPS (33, range 13-70) than systematic biopsies with higher GS (median GPS 25, range 15-55). Conclusions: GPS provides independent and complementary prognostic information to mpMRI-guided biopsies. The combination of mpMRI for biopsy guidance and GPS for molecular analysis may optimize prediction of AP and improve patient selection for treatment versus surveillance.