Gleason Grade Group Research Articles

Prostate Cancer–specific and All-cause Mortality After Robot-assisted Radical Prostatectomy: 20 Years’ Report from the European Association of Urology Robotic Urology Section Scientific Working Group

BackgroundEvidence on long-term oncological efficacy is available only for open radical prostatectomy but remains scarce for robot-assisted radical prostatectomy (RARP). ObjectiveTo validate the long-term survival rates after RARP and provide stratified outcomes based on contemporary prostate cancer (PCa) risk-stratification tools. Design, setting, and participantsA retrospective analysis of the European Association of Urology (EAU) Robotic Urology Section Scientific Working Group international multicenter database for RARP was performed. Patients who underwent RARP at seven pioneer robotic urology programs in Europe and the USA between 2002 and 2012 were included. Outcome measurements and statistical analysisThe primary outcomes were PCa-specific mortality and all-cause mortality. The probability of cancer-specific survival (CSS) was estimated with the competing risks method, and the probability of overall survival (OS) was estimated with the Kaplan-Meier method. Results and limitationsA total of 9876 patients who underwent RARP between 2002 and 2012 were included. Within follow-up, 1071 deaths occurred and 159 were due to PCa. At 15 yr of follow-up, CSS and OS were 97.6% (97.2%, 98.0%) and 85.5% (84.6%, 86.4%), respectively. Stratified analyses based on EAU risk groups at diagnosis and pT stage showed favorable survival rates, with low-risk (n = 4601, 46.6%), intermediate-risk (n = 4056, 41.1%), and high-risk (n = 1219, 12.3%) patients demonstrating CSS rates of 99%, 98%, and 90% at 15 yr, respectively. Notably, patients with pT3a disease had similar survival outcomes to those with pT2 disease, with worse CSS in patients with pT3b PCa (98.9% vs 97.4% vs 86.5%). Multivariable analyses identified age, prostate-specific antigen, biopsy Gleason grade group, clinical T stage, and treatment year as independent predictors of worse oncological outcomes. ConclusionsOur multicenter study with long-term follow-up confirms favorable survival outcomes after RARP for localized PCa. Patients with low- and intermediate-risk disease face a higher risk of mortality from causes other than PCa. On the contrary, high-risk patients have a significantly higher risk of PCa-specific mortality. Patient summaryIn the present study, we reported the outcomes of patients with prostate cancer (PCa) who underwent robot-assisted radical prostatectomy between 10 and 20 yr ago, and we found a very low probability of dying from PCa in patients with low- and intermediate-risk PCa.

A Prostate-Specific Membrane Antigen PET-Based Approach for Improved Diagnosis of Prostate Cancer in Gleason Grade Group 1: A Multicenter Retrospective Study.

The preoperative Gleason grade group (GG) from transrectal ultrasound-guided prostate biopsy is crucial for treatment decisions but may underestimate the postoperative GG and miss clinically significant prostate cancer (csPCa), particularly in patients with biopsy GG1. In such patients, an SUVmax of at least 12 has 100% specificity for detecting csPCa. In patients with an SUVmax of less than 12, we aimed to develop a model to improve the diagnostic accuracy of csPCa. Methods: The study retrospectively included 56 prostate cancer patients with transrectal ultrasound-guided biopsy GG1 and an SUVmax of less than 12 from 2 tertiary hospitals. All [68Ga]Ga-PSMA-HBED-CC PET scans were centrally reviewed in Xijing Hospital. A deep learning model was used to evaluate the overlap of SUVmax (size scale, 3 cm) and the level of Gleason pattern (size scale, 500 μm). A diagnostic model was developed using the PRIMARY score and SUVmax, and its discriminative performance and clinical utility were compared with other methods. The 5-fold cross-validation (repeated 1,000 times) was used for internal validation. Results: In patients with GG1 and an SUVmax of less than 12, significant prostate-specific membrane antigen (PSMA) histochemical score (H-score) H-score overlap occurred among benign gland, Gleason pattern 3, and Gleason pattern 4 lesions, causing SUVmax overlap between csPCa and non-csPCa. The model of 10 × PRIMARY score + 2 × SUVmax exhibited a higher area under the curve (AUC, 0.8359; 95% CI, 0.7233-0.9484) than that found using only the SUVmax (AUC, 0.7353; P = 0.048) or PRIMARY score (AUC, 0.7257; P = 0.009) for the cohort and a higher AUC (0.8364; 95% CI, 0.7114-0.9614) than that found using only the Prostate Imaging Reporting and Data System (PI-RADS) score of 5-4 versus 3-1 (AUC, 0.7036; P = 0.149) and the PI-RADS score of 5-3 versus 2-1 (AUC, 0.6373; P = 0.014) for a subgroup. The model reduced the misdiagnosis of the PI-RADS score of 5-4 versus 3-1 by 78.57% (11/14) and the PI-RADS score of 5-3 versus 2-1 by 77.78% (14/18). The internal validation showed that the mean 5-fold cross-validated AUC was 0.8357 (95% CI, 0.8357-0.8358). Conclusion: We preliminarily suggest that the model of 10 × PRIMARY score + 2 × SUVmax may enhance the diagnostic accuracy of csPCa in patients with biopsy GG1 and an SUVmax of less than 12 by maximizing PSMA information use, reducing the misdiagnosis of the PI-RADS score, and thereby aiding in making appropriate treatment decisions.

Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP presence. To develop deep learning models for detecting AP presence, and to compare the performance of these models with those of a clinical model (CM) and radiologists' interpretation (RI). Retrospective. Totally, 616 men from six institutions who underwent radical prostatectomy, were divided into a training cohort (508 patients from five institutions) and an external validation cohort (108 patients from one institution). T2-weighted imaging with a turbo spin echo sequence and diffusion-weighted imaging with a single-shot echo plane-imaging sequence at 3.0 T. The reference standard for AP was histopathological extracapsular extension, seminal vesicle invasion, or positive surgical margins. A deep learning model based on the Swin-Transformer network (TransNet) was developed for detecting AP. An integrated model was also developed, which combined TransNet signature with clinical characteristics (TransCL). The clinical characteristics included biopsy Gleason grade group, Prostate Imaging Reporting and Data System scores, prostate-specific antigen, ADC value, and the lesion maximum cross-sectional diameter. Model and radiologists' performance were assessed using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The Delong test was used to evaluate difference in AUC. P < 0.05 was considered significant. The AUC of TransCL for detecting AP presence was 0.813 (95% CI, 0.726-0.882), which was higher than that of TransNet (0.791 [95% CI, 0.702-0.863], P = 0.429), and significantly higher than those of CM (0.749 [95% CI, 0.656-0.827]) and RI (0.664 [95% CI, 0.566-0.752]). TransNet and TransCL have potential to aid in detecting the presence of AP and some single adverse pathologic features. 4 TECHNICAL EFFICACY: Stage 4.

Estimated absolute percentage of biopsied tissue positive for Gleason pattern 4 (eAPP4) in low dose rate prostate brachytherapy: Evaluation of prognostic utility in a large cohort

PurposeTo determine whether a system to estimate Absolute Percentage of Biopsied Tissue Positive for Gleason Pattern 4 (eAPP4) is useful as a prognostication tool for patients with intermediate risk prostate cancer (IR-PCa) undergoing low dose rate prostate brachytherapy. Methods497 patients with IR-PCa and known grade group 2 or 3 disease treated with low dose rate seed brachytherapy (LDR-BT) at a quaternary cancer centre were retrospectively reviewed. Prostate biopsies for each patient included Gleason grading with synoptic reporting that did not include percentage of pattern 4 disease found within the sample. Each core was assigned a grade grouping, however, and that was used with optimized estimates of percentage of pattern four disease to estimate eAPP4. Outcomes including cumulative incidence of recurrence (CIR), treatment of recurrent disease (RRX), and metastasis-free survival (MFS) were then reviewed and the prognostic value of eAPP4 evaluated. Results428 (86%) patients had Gleason grade group 2 and 69 (14%) patients had Gleason grade group 3 disease. 230 (46%) patients had National Comprehensive Cancer Network (NCCN) favourable intermediate at baseline, while 267 (54%) of patients had NCCN unfavourable intermediate at baseline. Median follow-up was 7.3 (5.5–9.6) years. eAPP4 was predictive of CIR (p = 0.003), RRX (p = 0.003), or MFS (p = 0.001) events, while Gleason grade grouping alone was not. eAPP4 was strongest as a predictor for MFS when estimates of 30% (grade group 2) and 80% (grade group 3) were used [HR 1.07 (1.03–1.12); p = 0.001]. ConclusionseAPP4 was strongly predictive of recurrence and metastasis-free survival in a large cohort of patients receiving LDR-BT treatment for IR-PCa. Treatment of future patients with IR-PCa could include the use of eAPP4 prognostication.

Patient experiences with tissue-based genomic testing during active surveillance for prostate cancer.

Tissue-based gene expression (genomic) tests provide estimates of prostate cancer aggressiveness and are increasingly used for patients considering or engaged in active surveillance. However, little is known about patient experiences with genomic testing and its role in their decision-making. We performed a qualitative study consisting of in-depth, semi-structured interviews of patients with low- or favourable-intermediate-risk prostate cancer managed with active surveillance. We purposively sampled to include patients who received biopsy-based genomic testing as part of clinical care. The interview guide focused on experiences with genomic testing during patients' decision-making for prostate cancer management and understanding of genomic test results. We continued interviews until thematic saturation was reached, iteratively created a code key and used conventional content analysis to analyse data. Participants' (n= 20) mean age was 68 years (range 51-79). At initial biopsy, 17 (85%) had a Gleason grade group 1, and 3 (15%) had a grade group 2 prostate cancer. The decision to undergo genomic testing was driven by both participants and physicians' recommendations; however, some participants were unaware that testing had occurred. Overall, participants understood the role of genomic testing in estimating their prostate cancer risk, and the test results increased their confidence in the decision for active surveillance. Participants had some misconceptions about the difference between tissue-based gene expression tests and germline genetic tests and commonly believed that tissue-based tests measured hereditary cancer risk. While some participants expressed satisfaction with their physicians' explanations, others felt that communication was limited and lacked sufficient detail. Patients interact with and are influenced by the results of biopsy-based genomic testing during active surveillance for prostate cancer, despite gaps in understanding about test results. Our findings indicate areas for improvement in patient counselling in order to increase patient knowledge and comfort with genomic testing.

The diagnostic effectiveness of serum sialic acid predicts both qualitative and quantitative prostate cancer in patients with prostate-specific antigen between 4 and 20 ng/mL.

This study aimed to evaluate the predictive value of the serum biochemical index, including alkaline phosphatase (AKP), lactate dehydrogenase (LDH), α-L-fucosidase (AFU), serum sialic acid (SA), and fibrinogen (FIB), for prostate cancer (PCa) and clinically significant prostate cancer (CSPCa) in patients with a prostate-specific antigen (PSA) value between 4 and 20 ng/mL. This study retrospectively examined the clinical data of 408 eligible patients who underwent prostate biopsies in our hospital between March 2015 and July 2022. CSPCa was defined as a "Gleason grade group of≥2". For analyzing the association between PCa/CSPCa and serum biochemical index, univariable logistic regression and multivariable logistic regression were conducted. Based on the multivariable logistic regression model, we constructed models and compared the area under the curve (AUC). We generated the nomogram, the ROC curve, the DCA curve, and the calibration curve for PCa. Overall, we studied 271 patients with PCa (including 155 patients with CSPCa) and 137 non-PCa patients. Patients with PCa were more likely to consume alcohol, have higher total PSA (TPSA) values, and have lower free PSA (FPSA) and free/total PSA (f/T) values. There were higher TPSA values and lower f/T values in the CSPCa group when compared with the non-CSPCa group. The univariate logistic regression analyses did not show significant results. However, AKP, AFU, SA, TPSA, and FPSA all retain significant significance when all factors are included in multifactor logistic regression analysis. This finding suggests that the exposure factor exhibited an independent effect on the outcome after controlling for other factors, including the potential confounding effects that may have been underestimated. Through ROC curves, we found that SA and TPSA levels are more powerful predictors. In contrast, there is a lack of excellent predictive value for PCA and CSPCa using Age, AFU, FIB, and FPSA. In our study, serum biochemical index is a potential prediction tool for PCa and CSPCa for patients with PSA values between 4 and 20 ng/mL. Additionally, the new serum biochemical index SA is also useful when diagnosing PCa and CSPCa, as we conclude in our study.

Evaluating the Learning Curve for In-office Freehand Cognitive Fusion Transperineal Prostate Biopsy

To define the learning curve of the in-office, freehand MRI-ultrasound cognitive fusion transperineal prostate biopsy (CTPB) by assessing cancer detection, biopsy core quantity and quality, procedure times, and complications over the initial experience. We reviewed 110 consecutive CTPB performed March 2021-September 2022 by a urologist inexperienced with the PrecisionPoint platform. The study period was divided into quarters to assess for temporal variation in outcomes. Univariable and multivariable analysis modeled the learning curve. Across quarters, there were no differences in the detection of clinically significant prostate cancer (Q1:50%, Q2:52%, Q3:50%, Q4:48%, P>.9) or Gleason grade group upgrading by targeted vs systematic biopsy (P=.6). Median procedure times improved with experience (Q1:17minutes, Q2:14minutes, Q3:12minutes, Q4:13minutes, P=.018). On multivariable analysis, procedure times decreased by 1minute per 20 cases (P<.001). On linear regression, CTPB procedure times approximated transrectal biopsy times after 90 cases (P<.001). The histopathologic core quality did not differ, as evidenced by consistent core length (P=.13) and presence of minimal fibromuscular tissue (P>.9). The most common complications, hematuria and hematospermia, were similar across quarters (P=.7, P=.3, respectively). There was a single episode of urinary retention and no reported infections. There is no evidence of a learning curve for CTPB as shown by consistent clinically significant prostate cancer detection, high-quality biopsy cores, and low complications. However, CTPB procedural times begin to approximate cognitive targeted transrectal biopsy times after 90 cases.

Comprehensive analysis of predictive factors for upstaging in intraprostatic cancer after radical prostatectomy: Different patterns of spread exist in lesions at different locations.

Accurate assessment of the clinical staging is crucial for determining the need for radical prostatectomy (RP) in prostate cancer (PCa). However, the current methods for PCa staging may yield incorrect results. This study aimed to comprehensively analyze independent predictors of postoperative upstaging of intraprostatic cancer. We conducted a retrospective analysis of data from intraprostatic cancer patients who underwent radical surgery between March 2019 and December 2022. Intraprostatic cancer was defined as a lesion confined to the prostate, excluding cases where multiparameter magnetic resonance imaging (mpMRI) showed the lesion in contact with the prostatic capsule. We assessed independent predictors of extraprostatic extension (EPE) and analyzed their association with positive surgical margin (PSM) status. In addition, based on the distance of the lesion from the capsule on mpMRI, we divided the patients into non-transition zone and transition zone groups for further analysis. A total of 500 patients were included in our study. Logistic regression analysis revealed that biopsy Gleason grade group (GG) (odds ratio, OR: 1.370, 95% confidence interval, CI: 1.093-1.718) and perineural invasion (PNI) (OR: 2.746, 95% CI: 1.420-5.309) were predictive factors for postoperative EPE. Both biopsy GG and PNI were associated with lateral (GG: OR: 1.270, 95% CI: 1.074-1.501; PNI: OR: 2.733, 95% CI: 1.521-4.911) and basal (GG: OR: 1.491, 95% CI: 1.194-1.862; PNI: OR: 3.730, 95% CI: 1.929-7.214) PSM but not with apex PSM (GG: OR: 1.176, 95% CI: 0.989-1.399; PNI: OR: 1.204, 95% CI: 0.609-2.381) after RP. Finally, PNI was an independent predictor of EPE in the transition zone (OR: 11.235, 95% CI: 2.779-45.428) but not in the non-transition zone (OR: 1.942, 95% CI: 0.920-4.098). PNI and higher GG may indicate upstaging of tumors in patients with intraprostatic carcinoma. These two factors are associated with PSM in locations other than the apex of the prostate. Importantly, cancer in the transition zone of the prostate is more likely to spread externally through nerve invasion than cancer in the non-transition zone.

Correlation of expression of Cyclin D1 and E-cadherin with gleason grade, serum prostate specific antigen levels and prostatic volume in prostatic carcinoma

Background: Prostate cancer is increasingly being diagnosed early due to easy access and availability of better diagnostic modalities. Gleason scoring is important for prognosis and is used to determine the management protocol. As the behavior of these tumors is unpredictable, many markers are being investigated. Cyclin D1 and E-Cadherin have been linked to the development, progression, and aggressiveness in some studies. We studied the expression of E cadherin and cyclin D1 in various grades to understand their relationship with clinicopathologic features, PSA, and prostatic volume. Material &amp; methods: 52 patients diagnosed with prostatic adenocarcinoma on core biopsy after ethical clearance in our tertiary care center were included in the study and their records were retrieved. Hematoxylin and Eosin stained sections were used for Gleason scoring as well as Gleason grade group as per existing protocols. Immunohistochemistry using antibodies against Cyclin D1 and E-Cadherin along with appropriate controls was performed. Studied parameters were correlated with E-Cadherin and cyclin D1. We used a statistical software package (version 22, IBM, US). Results: Cyclin D1 showed increasing immunoexpression with an increase in Gleason score and Gleason grade group emphasizing a significant correlation between these parameters (p= 0.001). There was a significant negative association between E-cadherin score, Gleason score, and Gleason grade group (p=0.001). No correlation was obtained with serum PSA or prostatic volume. Conclusions: E-cadherin and Cyclin D1 dysregulation could be used as prognostic and predictive markers in prostatic carcinoma.

Correlation between the Total Initial PSA , PSA Density, and Prostate Cancer Aggressiveness: A Retrospective Study In Two Urology Centers In Cameroon

Objectives: Our study aimed to determine the relationship between the initial total prostate-specific antigen (PSA), PSA density, and aggressiveness of prostate cancer (PCa) based on the new Gleason grade group in the two specialized urology centers in Cameroon. Method: A seven-year retrospective study was conducted from January 2012 to December 2019. The study concerned all men diagnosed with PCa graded using the novel Gleason grade group. Data were analyzed descriptively and analytically using Statistical Package for Social Sciences (SPSS) version 20.0. Bivariate analysis was done to identify independent associations. Results: A total of 253 files were reviewed; fulfilling the inclusion criteria. The mean age of our study population was 66.62±8.288 years with the most affected age being those aged between 59-69 years. The commonest finding on DRE was a hard-craggy prostate (46.0%). The mean initial total PSA was 98.78 ng/dL ± 300.17 ng/mL, while the mean PSA density was 1.73 ± 5.94ng/mL². Gleason grade group 2 was the commonest grade (30.6%). There was a positive correlation between initial total PSA and Gleason grade group (r = 0.314 (p-value 0.000)), and between PSA density and Gleason grade group (r = 0.919 (p-value 0.000)). Initial total PSA and the Gleason grade groups were independently associated with the radiological tumour stage (p-value 0.000 and p-value 0.03 respectively). Conclusion: There is a positive correlation between initial total PSA, PSA density, and novel Gleason grade group. We, therefore, recommend that more attention should be placed on PSA density in pre-biopsy decision making. This study enhances the stratification of therapeutic protocols for the management of PCa in Cameroon as well as across African Union member states.

Peritumoral Radiomics Strategy Based on Ensemble Learning for the Prediction of Gleason Grade Group of Prostate Cancer

To develop and evaluate a peritumoralradiomic-based machine learning model to differentiate low-Gleason grade group (L-GGG) and high-GGG (H-GGG) prostate lesions. In this retrospective study, a total of 175 patients with prostate cancer (PCa) confirmed by puncture biopsy were recruited and included 59 patients with L-GGG and 116 patients with H-GGG. The original PCa regions of interest (ROIs) were delineated on T2-weighted (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps, and then centra-tumoral and peritumoral ROIs were defined. Features were meticulously extracted from each ROI to establish radiomics models, employing distinct sequence datasets. Peritumoral radiomics models were specifically developed for both the peripheral zone (PZ) and transitional zone (TZ), utilizing dedicated PZ and TZ datasets, respectively. The performances of the models were evaluated by using the receiver operating characteristic (ROC) curve and precision-recall curve. The classification model with combined peritumoral features based on T2+DWI+ADC sequence dataset demonstrated superior performance compared to the original tumor and centra-tumoral classification models. It achieved an area under the ROC curve (AUC) of 0.850 [95% confidence interval, 0.849, 0.860] and an average accuracy of 0.950. The combined peritumoral model outperformed the regional peritumoral models with AUC of 0.85 versus 0.75 for PZ lesions and 0.88 versus 0.69 for TZ lesions, respectively. The peritumoral classification models exhibit greater efficacy in predicting PZ lesions as opposed to TZ lesions. The peritumoral radiomics features showed excellent performance in predicting GGG in PCa patients and might be a valuable addition to the non-invasive assessment of PCa aggressiveness.

Outlook of Gleason score in prostate carcinoma and correlation with PSA levels: A study in a tertiary care hospital.

In India, prostate carcinoma is the fifth most common cause of carcinoma in men, and the fourth in cancer mortality. Incidence of prostate malignancy is increasing in India by one percent every year. Prostate carcinoma is graded using the Gleason scoring system. The Gleason score is very useful for predicting the prognosis of prostate carcinoma. The collaborative use of clinical features, combined with the size of the prostate, prostate-specific antigen levels, and histopathological features helps in making an accurate and early diagnosis of the patients. This present prospective study included all histologically proven cases of prostate carcinoma in the Department of Pathology, Guru Gobind Singh Medical Hospital over a period of one year. A detailed histopathological examination of the H and E stained sections is carried out under light microscope including histological typing, Gleason scoring and grading. The Gleason grade was correlated with serum PSA levels. Out of 80 cases, 28 (35%) were reported as Gleason grade group 3 with a Gleason score of 7 (4 + 3). 12 cases (15%) showed a Gleason grade group 2 with a Gleason score of 7 (3 + 4). Grade group 4 (Gleason score 8) and grade group 5 were observed in 22 cases (27.5%) and 18 cases (22.5%), respectively. Whereas, no case of Gleason grade group 1 with Gleason score of 6 (3 + 3) was seen. Gleason's Group Grade 3 outnumbered all the group grades, contributing 35% (28 cases) of the total cases of prostatic adenocarcinoma. Serum PSA levels were raised (>10 ng/ml) in 100% of cases. Henceforth, it signifies the importance of serum PSA levels in prostate carcinoma. Lymphovascular invasion was associated with higher group grade of prostatic adenocarcinoma.

Prostate cancer detection and segmentation on MRI using non-local mask R-CNN with histopathological ground truth.

Automatic detection and segmentation of intraprostatic lesions (ILs) on preoperative multiparametric-magnetic resonance images (mp-MRI) can improve clinical workflow efficiency and enhance the diagnostic accuracy of prostate cancer and is an essential step in dominant intraprostatic lesion boost. The goal is to improve the detection and segmentation accuracy of 3D ILs in MRI by a proposed a deep learning (DL)-based algorithm with histopathological ground truth. This retrospective study included 262 patients with in vivo prostate biparametric MRI (bp-MRI) scans and were divided into three cohorts based on their data analysis and annotation. Histopathological ground truth was established by using histopathology images as delineation reference standard on cohort 1, which consisted of 64 patients and was randomly split into 20 training, 12 validation, and 32 testing patients. Cohort 2 consisted of 158 patients with bp-MRI based lesion delineation, and was randomly split into 104 training, 15 validation, and 39 testing patients. Cohort 3 consisted of 40 unannotated patients, used in semi-supervised learning. We proposed a non-local Mask R-CNN and boosted its performance by applying different training techniques. The performance of non-local Mask R-CNN was compared with baseline Mask R-CNN, 3D U-Net and an experienced radiologist's delineation and was evaluated by detection rate, dice similarity coefficient (DSC), sensitivity, and Hausdorff Distance (HD). The independent testing set consists of 32 patients with histopathological ground truth. With the training technique maximizing detection rate, the non-local Mask R-CNN achieved 80.5% and 94.7% detection rate; 0.548 and 0.604 DSC; 5.72 and 6.36 95 HD (mm); 0.613 and 0.580 sensitivity for ILs of all Gleason Grade groups (GGGs) and clinically significant ILs (GGG>2), which outperformed baseline Mask R-CNN and 3D U-Net. For clinically significant ILs, the model segmentation accuracy was significantly higher than that of the experienced radiologist involved in the study, who achieved 0.512 DSC (p=0.04), 8.21 (p=0.041) 95 HD (mm), and 0.398 (p=0.001) sensitivity. The proposed DL model achieved state-of-art performance and has the potential to help improve radiotherapy treatment planning and noninvasive prostate cancer diagnosis.

A national questionnaire survey of Japanese urologists on treatment perspectives for elderly prostate cancer patients.

This study conducted a national questionnaire survey of Japanese urologists from a treatment perspective for older patients with prostate cancer. A questionnaire was distributed to 922 teaching hospitals of the Japanese Urological Association. Questionnaire items included years of urologist experience, gender, workplace, treatment equipment owned, daily specialty practice area, urological cancer specialty, treatment reference items for older adults, upper age limit for radical treatment, medication, and two hypothetical cases of Gleason grade group 2 prostate cancer with or without oligometastasis. In total, 1732 questionnaires were analyzed, with responses evenly distributed across all age groups. Workplaces included general hospitals (49.4%), university hospitals (40.3%), and cancer centers (4.2%). Performance status was the most frequently mentioned treatment-related item, followed by comorbidities and cognitive function. In addition, geriatric assessment was used by only 13.3% of respondents. No upper age limit was found for total prostatectomy, brachytherapy, and external beam radiation. Anti-androgens, androgen receptor-axis-targeted agents, chemotherapy, poly ADP ribose polymerase inhibitors, and immune-checkpoint inhibitors were selected by 6.8%, 35.6%, 47.3%, 89%, 62.8%, 24.7%, 41.9%, and 41.7% of the respondents, respectively. Response rates for administration of hormone therapy for hypothetical cases of Gleason grade group 2 prostate cancer with or without oligometastases were 96.8% and 61.2%, respectively. Less than 15% of urologists used geriatric assessments. Several responded that they would set age limits for highly invasive radical and systemic therapies.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer

BackgroundProstate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression.MethodsWe analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan–Meier estimator, log-rank test, and Cox regression.ResultsOur analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05).ConclusionsOur gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

Analysis of the surgical approach in prostate cancer staging: results from the surveillance, epidemiology and end results program

Surgery is not used as a criterion for staging prostate cancer, although there is evidence that the number of analyzed and affected lymph nodes have prognosis value. The aim of this study was to determine whether there are significant differences in staging criteria in patients who underwent prostatectomy compared to those who did not, and whether the number of affected and analyzed lymph nodes (LN) plays a prognostic role. In this retrospective study, a test cohort consisting of 404,210 newly diagnosed men with prostate cancer, between 2004 and 2010, was obtained from the 17 registries (Nov 2021 submission); a validation consisting of 147,719 newly diagnosed men with prostate cancer between 2004 and 2019 was obtained from the 8 registries (Nov 2021 submission). Prostate cancer-specific survival was analyzed by Kaplan–Meier curves, survival tables and Cox regression; overall survival was analyzed only to compare Harrell's C-index between different staging criteria. In initial analyses, it was observed that the prognostic value of lymph node metastasis changes according to the type of staging (clinical or pathological), which is linked to the surgical approach (prostatectomy). Compared with T4/N0/M0 patients, which are also classified as stage IVA, N1/M0 patients had a shorter [adjusted HR: 1.767 (1429–2184), p < 0.0005] and a longer [adjusted HR: 0.832 (0.740–0.935), p = 0.002] specific survival when submitted to prostatectomy or not, respectively. Analyzing separately the patients who were submitted to prostatectomy and those who were not, it was possible to obtain new LN metastasis classifications (N1: 1 + LN; N2: 2 + LNs; N3: > 2 + LNs). This new (pathological) classification of N allowed the reclassification of patients based on T and Gleason grade groups, mainly those with T3 and T4 disease. In the validation group, this new staging criterion was proven to be superior [specific survival C-index: 0.908 (0.906–0.911); overall survival C-index: 0.788 (0.786–0.791)] compared to that currently used by the AJCC [8th edition; specific survival C-index: 0.892 (0.889–0.895); overall survival C-index: 0.744 (0.741–0.747)]. In addition, an adequate number of dissected lymph nodes results in a 39% reduction in death risk [adjusted HR: 0.610 (0.498–0.747), p < 0.0005]. As main conclusion, the surgery has a major impact on prostate cancer staging, mainly modifying the effect of N on survival, and enabling the stratification of pathological N according to the number of affected LN. Such a factor, when considered as staging criteria, improves the prognosis classification.

Development and validation of nomogram to improve the specificity of multiparametric MRI for clinically significant prostate cancer.

To develop and validate a nomogram to improve the specificity of prostate imaging reporting and data system (PI-RADS) on multiparametric magnetic resonance imaging (MRI) for clinically significant prostate cancer on targeted fusion biopsy. A retrospective review of patients who underwent fusion biopsy for PI-RADS 3-5 lesions using UroNav and Artemis systems between 2016 and 2022 was performed. Patients were divided into those with CS disease on fusion biopsy (Gleason grade group ≥2) versus those without. Multivariable analysis was used to identify variables associated with CS disease. A 100-point nomogram was constructed, and ROC curve was generated. 1485 lesions (1032 patients) were identified, 510 (34%) were PI-RADS 3, 586 (40%) were PI-RADS 4, and 389 (26%) were PI-RADS 5. Of these, 11% of PI-RADS 3, 39% of PI-RADS 4, and 61% of PI-RADS 5 showed CS disease. CS disease was associated with older age (OR 1.04, 95% CI 1.02-1.06, p < 0.01), previous negative biopsy (OR 0.52, 95% CI 0.36-0.74, p < 0.01), presence of multiple PI-RADS 3-5 lesions (OR 0.61, 95% CI 0.45-0.83, p < 0.01), peripheral zone location (OR 1.88, 95% CI 1.30-2.70, p < 0.01), PSA density (OR 1.48 per 0.1 unit, 95% CI 1.33-1.64, p < 0.01), PI-RADS score 4 (OR 3.28, 95% CI 2.21-4.87, p < 0.01), and PI-RADS score 5 (OR 7.65, 95% CI 4.93-11.85, p < 0.01). Area under ROC curve was 82% for nomogram compared to 75% for PI-RADS score alone. We report a nomogram that combines PI-RADS score with other clinical parameters. The nomogram outperforms PI-RADS score for the detection of CS prostate cancer.

Impact of prostate radiotherapy on survival outcomes in clinically node-positive prostate cancer: A multicentre retrospective analysis

PurposeTo evaluate clinical outcomes for cN1M0 prostate cancer treated with varied modalities. Materials and methodsMen with radiological stage cN1M0 prostate cancer on conventional imaging, treated from 2011-2019 with various modalities across four centres in the UK were included. Demographics, tumour grade and stage, and treatment details were collected. Biochemical and radiological progression-free survival (bPFS, rPFS) and overall survival (OS) were estimated using Kaplan Meier analyses. Potential factors impacting survival were tested with univariable log-rank test and multivariable Cox-proportional hazards model. ResultsTotal 337 men with cN1M0 prostate cancer were included, 47% having Gleason grade group 5 disease. Treatment modalities included androgen deprivation therapy (ADT) in 98.9% men, either alone (19%) or in combinations including prostate radiotherapy (70%), pelvic nodal radiotherapy (38%), docetaxel (22%), or surgery (7%). At median follow up of 50 months, 5-year bPFS, rPFS, and OS were 62.7%, 71.0%, and 75.8% respectively. Prostate radiotherapy was associated with significantly higher bPFS (74.1% vs 34.2%), rPFS (80.7% vs 44.3%) and OS (86.7% vs 56.2%) at five years (log rank p < 0.001 each). On multivariable analysis including age, Gleason grade group, tumour stage, ADT duration, docetaxel, and nodal radiotherapy, benefit of prostate radiotherapy persisted for bPFS [HR 0.33 (95% CI 0.18–0.62)], rPFS [HR 0.25 (0.12–0.51)], and OS [HR 0.27 (0.13–0.58)] (p < 0.001 each). Impact of nodal radiotherapy or docetaxel was not established due to small subgroups. ConclusionAddition of prostate radiotherapy to ADT in cN1M0 prostate cancer yielded improved disease control and overall survival independent of other tumour and treatment factors.

Biopsy Assessment of Oncologic Control 3 Years Following Primary Partial Gland Cryoablation: A Prospective Cohort Study of Men With Intermediate-risk Prostate Cancer.

We evaluated 3-year oncologic outcomes following primary partial gland cryoablation. Men with unilateral intermediate-risk prostate cancer undergoing primary partial gland cryoablation since March 2017 enrolled in a prospective outcome registry. The postablation protocol for all men included surveillance prostate biopsy at 2 years postablation and reflex prostate biopsy for cases with high suspicion of recurrence (eg, progressive rise in PSA). Recurrence of clinically significant prostate cancer was defined as any Gleason grade group ≥2 disease on postablation biopsy. Freedom from failure represented no whole gland salvage treatment, metastatic prostate cancer, or prostate cancer mortality. Freedom from recurrence and freedom from failure were characterized using nonparametric maximum likelihood estimators. A total of 132 men had at least 24 months of follow-up data. Biopsies identified clinically significant prostate cancer in 12 men. At 36 months, model-estimated rates of freedom from recurrence of in-field, out-of-field, and overall clinically significant cancer were 97% (95% CI: 92-100), 87% (95% CI: 80-94), and 86% (95% CI: 78-93), respectively. The model-estimated proportion with freedom from failure at 36 months was 97% (95% CI: 93-100). The low in-field cancer detection rate at 3 years indicates successful ablation of localized cancers. Conversely, our observed out-of-field detection rate highlights the need for continued surveillance following partial gland cryoablation. Many of these recurrences exhibited very low volume of clinically significant disease below the detection threshold of multiparametric MRI, suggesting a limited role for multiparametric MRI in detecting clinically significant recurrences at 2 years. These findings emphasize the need for long-term surveillance and identification of predictors of clinically significant prostate cancer recurrences to guide biopsy timing.

Abstract B048: Performance of diagnostic biomarkers in the Canary Prostate cancer Active Surveillance Study (PASS)

Abstract Introduction Many biomarker assays improve sensitivity in diagnosing high grade prostate cancer (PCa), but their performance during active surveillance, after a diagnosis of PCa, is not well understood. Procedures In the multicenter Canary PASS cohort, we explored the contribution of four distinct biomarker panels (blood-based: 4Kpanel, phi; urine-based: PCA3, MDxSelect RNA) and clinical variables in predicting 4-year extreme biopsy reclassification to Gleason Grade Group 3 (GG3) or above. Biomarker assays were performed between 2014-2020 on subcohorts including 727-1,176 participants; outcomes were collected through March 2020. Models were built using a) biomarker, b) biomarker + prostate volume, c) biomarker + biopsy variables d) biomarker + prostate volume + biopsy variables, and, for urine markers e) biomarker + prostate volume + biopsy variables + serum PSA. Clinical PSA was used as a reference. Partly conditional Cox proportional hazards regression models for residual time to event were constructed based on information available at each prediction time, accounting for competing risk. The probability of extreme reclassification within 4 years was calculated after diagnosis and after first follow-up biopsy (Bx1) and the accuracy was assessed with the cross-validated receiver operating characteristic (ROC) curve analysis. Results Cross validated Areas Under the Curve (AUCs) for predictions made with biomarkers ranged from 0.648 (95% CI: 0.581, 0.716) to 0.755 (95% CI: 0.687, 0.824) after diagnosis and from 0.588 (95% CI: 0.480, 0.696) to 0.669 (95% CI: 0.558, 0.780) after Bx1, and were consistently higher than AUCs for clinical PSA at both timepoints; the difference in AUC between biomarker and PSA was statistically significant only for 4Kpanel and phi. Adding clinical variables to predictive models improved AUCs to varying degrees; AUCs for full models with all variables were 0.702 (95% CI: 0.641, 0.764) to 0.776 (95% CI: 0.715, 0.837) after diagnosis and 0.740 (95% CI: 0.656, 0.824) to 0.763 (95% CI: 0.691, 0.836) after Bx1. Adding clinical variables to blood biomarkers resulted in less incremental improvement than for urine markers. A limitation of this study is that prostate MRI was not part of the PASS protocol, although MRI data collected suggests minimal predictive ability during active surveillance. Conclusions Our results suggest that early during prostate cancer active surveillance the blood-based biomarkers of the 4Kpanel and phi may predict future reclassification to higher grade cancer as well as or better than common clinical variables. Clinical variables improve the performance of the urine-based markers of PCA3 or MDxSelect. External validation studies are needed. Citation Format: Lisa F. Newcomb, Yingye Zheng, Menghan Liu, James D. Brooks, Peter R. Carroll, Atreya Dash, William J. Ellis, Christopher J. Filson, Martin E. Gleave, Michael A. Liss, Frances M. Martin, Todd M. Morgan, Peter S. Nelson, Andrew A. Wagner, Daniel W. Lin. Performance of diagnostic biomarkers in the Canary Prostate cancer Active Surveillance Study (PASS) [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B048.