Extreme-hypofractionated RT with concomitant boost to the DIL in PCa: a 5-year update on oncological and patient-reported outcomes for the phase II trial "GIVE ME FIVE".

AIM: The present work reports updated oncological results and patients-reported outcomes at 5 years of phase II trial "Short-term high precision RT for early prostate cancer with SIB to the dominant intraprostatic lesion (DIL) for patients with early-stage PCa". METHODS: Data from patients enrolled within AIRC IG-13218 (NCT01913717) trial were analyzed. Clinical and GU/GI toxicity assessment and PSA measurements were performed every 3 months for at least 2 years after RT end. QoL of enrolled patients was assessed by IPSS, EORTC QLQ-C30, EORTC QLQ-PR25, and IIEF-5. Patients' score changes were calculated at the end of RT and at 1, 12, and 60 months after RT. RESULTS: A total of 65 patients were included. At a median follow-up of 5 years, OS resulted 86%. Biochemical and clinical progression-free survival at 5 years were 95%. The median PSA at baseline was 6.07 ng/ml, while at last follow-up resulted 0.25 ng/ml. IPSS showed a statistically significant variation in urinary function from baseline (p = 0.002), with the most relevant deterioration 1 month after RT, with a recovery toward baseline at 12 months (p ≤ 0.0001). A numerical improvement in QoL according to the EORTC QLQ-C30 has been reported although not statistically significant. No change in sexual activity was recorded after RT. CONCLUSIONS: The study confirms that extreme hypofractionation with a DIL boost is safe and effective, with no severe effects on the QoL. The increasing dose to the DIL does not worsen the RT toxicity, thus opening the possibility of an even more escalated treatment.

Can we predict pathology without surgery? Weighing the added value of multiparametric MRI and whole prostate radiomics in integrative machine learning models.

OBJECTIVE: To test the ability of high-performance machine learning (ML) models employing clinical, radiological, and radiomic variables to improve non-invasive prediction of the pathological status of prostate cancer (PCa) in a large, single-institution cohort. METHODS: Patients who underwent multiparametric MRI and prostatectomy in our institution in 2015-2018 were considered; a total of 949 patients were included. Gradient-boosted decision tree models were separately trained using clinical features alone and in combination with radiological reporting and/or prostate radiomic features to predict pathological T, pathological N, ISUP score, and their change from preclinical assessment. Model behavior was analyzed in terms of performance, feature importance, Shapley additive explanation (SHAP) values, and mean absolute error (MAE). The best model was compared against a naïve model mimicking clinical workflow. RESULTS: The model including all variables was the best performing (AUC values ranging from 0.73 to 0.96 for the six endpoints). Radiomic features brought a small yet measurable boost in performance, with the SHAP values indicating that their contribution can be critical to successful prediction of endpoints for individual patients. MAEs were lower for low-risk patients, suggesting that the models find them easier to classify. The best model outperformed (p ≤ 0.0001) clinical baseline, resulting in significantly fewer false negative predictions and overall was less prone to under-staging. CONCLUSIONS: Our results highlight the potential benefit of integrative ML models for pathological status prediction in PCa. Additional studies regarding clinical integration of such models can provide valuable information for personalizing therapy offering a tool to improve non-invasive prediction of pathological status. CLINICAL RELEVANCE STATEMENT: The best machine learning model was less prone to under-staging of the disease. The improved accuracy of our pathological prediction models could constitute an asset to the clinical workflow by providing clinicians with accurate pathological predictions prior to treatment. KEY POINTS: • Currently, the most common strategies for pre-surgical stratification of prostate cancer (PCa) patients have shown to have suboptimal performances. • The addition of radiological features to the clinical features gave a considerable boost in model performance. Our best model outperforms the naïve model, avoiding under-staging and resulting in a critical advantage in the clinic. •Machine learning models incorporating clinical, radiological, and radiomics features significantly improved accuracy of pathological prediction in prostate cancer, possibly constituting an asset to the clinical workflow.

Comparison of automated segmentation techniques for magnetic resonance images of the prostate.

BACKGROUND: Contouring of anatomical regions is a crucial step in the medical workflow and is both time-consuming and prone to intra- and inter-observer variability. This study compares different strategies for automatic segmentation of the prostate in T2-weighted MRIs. METHODS: This study included 100 patients diagnosed with prostate adenocarcinoma who had undergone multi-parametric MRI and prostatectomy. From the T2-weighted MR images, ground truth segmentation masks were established by consensus from two expert radiologists. The prostate was then automatically contoured with six different methods: (1) a multi-atlas algorithm, (2) a proprietary algorithm in the Syngo.Via medical imaging software, and four deep learning models: (3) a V-net trained from scratch, (4) a pre-trained 2D U-net, (5) a GAN extension of the 2D U-net, and (6) a segmentation-adapted EfficientDet architecture. The resulting segmentations were compared and scored against the ground truth masks with one 70/30 and one 50/50 train/test data split. We also analyzed the association between segmentation performance and clinical variables. RESULTS: The best performing method was the adapted EfficientDet (model 6), achieving a mean Dice coefficient of 0.914, a mean absolute volume difference of 5.9%, a mean surface distance (MSD) of 1.93 pixels, and a mean 95th percentile Hausdorff distance of 3.77 pixels. The deep learning models were less prone to serious errors (0.854 minimum Dice and 4.02 maximum MSD), and no significant relationship was found between segmentation performance and clinical variables. CONCLUSIONS: Deep learning-based segmentation techniques can consistently achieve Dice coefficients of 0.9 or above with as few as 50 training patients, regardless of architectural archetype. The atlas-based and Syngo.via methods found in commercial clinical software performed significantly worse (0.855[Formula: see text]0.887 Dice).

What is the best time for postoperative radiation therapy in pN1 prostate cancer?

We retrospectively compared long-term biochemical recurrence rates (BCR) in pN1 PCa patients that underwent adjuvant radiotherapy (aRT) vs. no aRT/early salvage (esRT) after robot-assisted radical prostatectomy and extended pelvic lymphadenectomy. All PCa pN1 M0 patients treated at a single high-volume center between 2010 and 2020 were analyzed. Patients with <10 LNs yield, or >10 positive LNs, or persistently detectable PSA after RARP were excluded. Kaplan-Meier (KM) plots depicted BCR rates. Multivariable Cox regression models (MCRMs) focused on predictors of BCR. The cumulative incidence plot depicted BCR rates after propensity score (PS) matching (ratio 1:1). 220 pN1 patients were enrolled, 133 (60.4%) treated with aRT and 87 (39.6%) with no-aRT/esRT. aRT patients were older, with higher rates of postoperative ISUP grade group 4-5, and higher rates of pT3b stage. The actuarial BCR was similar (aRT 39.8% vs. no-aRT/esRT 40.2%; p=1). Median time to BCR was 62 vs. 38 months in aRT vs. no-aRT/esRT patients (p=0.001). In MCRMs, patients managed with no-aRT/esRT were associated with higher rates of BCR over time (hazard ratio [HR]: 3.27, p<0.001). ISUP grade group 5 (HR: 2.18, p<0.01) was an independent predictor of BCR. In PS-matched cumulative incidence plots, the BCR rate was significantly higher in the aRT group (76.4 vs. 40.4%; p<0.01). Patients managed with no-aRT/esRT experienced BCR approximately two years before the aRT group. Despite, the important BCR benefit after aRT, this treatment strategy is underused in daily practice.

Correlation between radiological and biological features and clinical outcomes in early prostate cancer: an exploratory subgroup analysis.

PTEN deletion and Ki-67 expression are two of the most promising biomarkers in prostate cancer (PCa). In the same manner, multiparametric magnetic resonance imaging (mp-MRI) guided core biopsy is a powerful tool for PCa detection and staging. The aim of the study is to assess whether a correlation can be identified between the pathological stage defined by an mp-MRI-guided core biopsy and Ki-67 expression and PTEN deletion. Such correlation might be useful for staging and treatment personalization in PCa. This investigation was conducted in the context of phase II clinical study "Short-term radiotherapy for early prostate cancer with a concomitant boost to the dominant lesion" (AIRC IG-13218), ClinicalTrials.gov identifier: NCT01913717. Nineteen patients underwent a further in-bore MRI-targeted core biopsy (MRI-TBx) on the dominant intraprostatic lesion (DIL); on this basis, an additional Gleason Score (GS) was determined. PTEN loss and Ki-67 expression on these samples were analyzed and correlated with both risk categories modifications and oncological outcomes (overall survival, biochemical and clinical relapse). GS was upgraded in 5 cases, with 4 patients re-classified as intermediate-risk and 1 patient as high-risk. The latter experienced a clinical local relapse. No correlations between up/down-staging, PTEN deletion, and Ki-67 expression were observed in this cohort. Further investigations are needed towards the identification of a pattern in the tumor aggressiveness-response in PCa treated with ultra-hypofractionated radiotherapy. Moreover, a possible relationship between biomarker analysis and imaging textural features could be explored.

Increased Body Mass Index Is a Risk Factor for Poor Clinical Outcomes after Radical Prostatectomy in Men with International Society of Urological Pathology Grade Group 1 Prostate Cancer Diagnosed with Systematic Biopsies.

INTRODUCTION: The association between obesity and clinically significant prostate cancer (PCa) is still a matter of debate. In this study, we evaluated the effect of body mass index (BMI) on the prediction of pathological unfavorable disease (UD), positive surgical margins (PSMs), and biochemical recurrence (BCR) in patients with clinically localized (≤cT2c) International Society of Urological Pathology (ISUP) grade group 1 PCa at biopsy. METHODS: 427 patients with ISUP grade group 1 PCa who have undergone radical prostatectomy and BMI evaluation were included. The outcome of interest was the presence of UD (defined as ISUP grade group ≥3 and pT ≥3a), PSM, and BCR. RESULTS: Statistically significant differences resulted in comparing BMI with prostate-specific antigen (PSA) and serum testosterone levels (both p < 0.0001). Patients with UD and PSM had higher BMI values (p < 0.0001 and p = 0.006, respectively). BCR-free survival was significantly decreased in patients with higher BMI values (p < 0.0001). BMI was an independent risk factor for BCR and PSM. Receiver-operating characteristic analysis testing PSA accuracy in different BMI groups, showed that PSA had a reduced predictive value (area under the curve [AUC] = 0.535; 95% confidence interval [CI] = 0.422-0.646), in obese men compared to overweight (AUC = 0.664; 95% CI = 0.598-0.725) and normal weight patients (AUC = 0.721; 95% CI = 0.660-0.777). CONCLUSION: Our findings show that increased BMI is a significant predictor of UD and PSM at RP in patients with preoperative low-to intermediate-risk diseases, suggesting that BMI evaluation may be useful in a clinical setting to identify patients with favorable preoperative disease characteristics harboring high-risk PCa.

Survival of contemporary patients with non-metastatic urachal vs. non-urachal adenocarcinoma of the urinary bladder.

PURPOSE: To test the effect of tumor location (urachal vs. non-urachal) on cancer-specific mortality (CSM) in patients with adenocarcinoma of the urinary bladder (ADKUB). MATERIALS AND METHODS: Within the Surveillance, Epidemiology, and End Results registry (2004-2016), we identified patients with non-metastatic (≤ T4N0M0) ADKUB. Stratification was made according to tumor location: urachal vs. non-urachal ADKUB. Kaplan-Meier plots and multivariable Cox regression models were fitted before and after 1:3 propensity score (PS) matching and separate Cox regression models were refitted before and after inverse probability of treatment weighting (IPTW). RESULTS: Of 1681 patients, 226 (13.5%) vs. 1455 (86.5%) harboured urachal vs. non-urachal ADKUB, respectively. Five-year cancer-specific survival (CSS) rates were, respectively, 75 vs. 67% for urachal vs. non-urachal ADKUB (p = 0.001). In subgroup analyses of ≤ T2N0M0 patients, 5-year CSS rates were, respectively, 84 vs. 73% for urachal vs. non-urachal ADKUB (p = 0.006). In subgroup analyses of T3-4N0M0 patients, 5-year CSS rates were, respectively, 68 vs. 49% for urachal vs. non-urachal ADKUB (p < 0.001). In multivariable Cox regression models, urachal ADKUB was associated with lower CSM rates (HR 0.6; p = 0.01). Virtually, the same findings were recorded after 1:3 PS matching (HR 0.6; p = 0.009) as well as when Cox regression models were refitted after IPTW (HR 0.7; p = 0.01). CONCLUSION: The distinction between urachal vs. non-urachal ADKUB indicates better prognosis when the origin of the tumor is urachal, regardless of methodological approach used for the comparison.

Conditional survival of patients with stage I-III squamous cell carcinoma of the penis: temporal changes in cancer-specific mortality.

PURPOSE: To test the conditional survival that examined the effect of event-free survival on cancer-specific mortality after primary tumour excision (PTE) in patients with squamous cell carcinoma of the penis (SCCP). MATERIALS AND METHODS: Within the SEER database (1998-2015), 2282 stage I-III SCCP patients were identified. Conditional survival estimates were used to calculate cancer-specific mortality (CSM) after event-free survival intervals of 1, 2, 3, and 5 years. Multivariable Cox regression models predicted CSM according to event-free survival. RESULTS: After PTE, 5-year CSM-free rate was 78.0% and increased to 84.6%, 88.1%, 92.0%, and 94.2% in patients who survived ≥ 1, ≥ 2, ≥ 3, and ≥ 5 years. After stratification according to tumour characteristics, 5-year CSM-free rates increased from 85.9 to 95.4%, 79.0 to 97.1%, 78.9 to 90.0%, and from 54.5 to 86.0% in those survived ≥ 5 years, respectively, in T1N0, T2N0, T3N0, and N1-2 patients. In multivariable analyses, T2N0 [hazard ratio (HR) 1.68; p value < 0.001], T3N0 (HR 1.94; p value 0.001), and N1-2 (HR 6.61; p value < 0.001) were independent predictors of higher CSM rate at baseline, relative to T1N0. A decrease in all HRs was assessed over time in patients who survived. Attrition due to CSM was highest in N1-2 cohort and lowest in T1N0. CONCLUSIONS: Conditional survival models showed a direct relationship between event-free survival duration and subsequent CSM in SCCP patients. Even patients with non-organ-confined disease may achieve survival probabilities similar to those with organ-confined disease after at least 5 years of event-free survival since PTE.

Insertion of a testicular prosthesis at the time of radical orchiectomy for testicular cancer is safe in patients who will subsequently undergo chemotherapy or radiotherapy.

We aimed to assess the incidence of prosthesis-related complications in patients who received a testicular prosthesis at the time of radical orchiectomy for testicular cancer and were then treated with chemotherapy (ChT) or radiotherapy (RT). We reviewed the records of the patients who underwent radical orchiectomy at our Institute since 1999; we also retrieved data from patients who underwent surgery elsewhere and then received ChT or RT at our Institution since 1999. We used the chi-square test to evaluate differences in the incidence of prosthesis-related complications between the groups. We retrieved the records of 587 patients; 393 had a testicular prosthesis implanted. Median follow-up was 57.7 months. One hundred thirty-eight patients (35.11%) received ChT, 129 RT (38.82%) and 10 (2.55%) both ChT and RT; of them, 6 (4.34%), 8 (6.20%) and 0 reported problems respectively. Seven (6.03%) of the 116 patients (29.52%) who had no further treatment had complications. The incidence of complications was not significantly different between patients who had no further treatment versus patients who underwent ChT (p = .75) or RT (p = .83). Testicular prosthesis insertion at the time of radical orchiectomy is safe even in patients subsequently undergoing ChT or RT.

Radioablation +/- hormonotherapy for prostate cancer oligorecurrences (Radiosa trial): potential of imaging and biology (AIRC IG-22159).

BACKGROUND: Prostate cancer (PCa) is the second most common cancer among men. New imaging-modalities have increased the diagnosed patients with limited number of metastasis after primary curative therapy, introducing so-called oligometastatic state. Stereotactic body radiotherapy (SBRT) is emerging as a low-toxicity treatment to erase PCa localizations and postpone androgen deprivation therapy (ADT). A deeper understanding of the predictive role of biomarkers is desirable for a targeted treatment selection and surveillance programs. The aims of the RADIOSA trial are: 1. Compare SBRT +/- ADT for oligorecurrent-castration-sensitive PCa (OCS-PCa) in terms of efficacy, toxicity and Quality of Life (QoL). 2. Develop biology/imaging based prognostic tool that allows identifying OCS-PCa subclasses. METHODS: This is a randomized phase II clinical trial, recruiting 160 OCS-PCa in 3 years, with progression-free survival (PFS) as primary endpoint. Three tasks will be developed: 1. Randomized clinical study (3 years for accrual and 2 years for follow-up and data analysis); 2. Imaging study, including imaging registration and METastasis Reporting and Data System (MET-RADS) criteria; 3. Pre-clinical study, development of a biobank of blood samples for the analysis of neutrophil-to-lymphocyte ratio and preparatory for a subsequent miRNA profiling. We aim to determine which arm is justified for testing in a subsequent Phase III trial. A decision-tree algorithm, based on prognosis, biological phenotype and imaging profile, will be developed. DISCUSSION: Recruiting will start in July 2019. SBRT will allow obtaining excellent PFS, local control, QoL and low toxicity. In SBRT arm, ADT deferral will allow for a drug-holiday, delaying the detrimental impact on QoL. A sufficient number of blood samples will be collected to perform biological patient profiling. A stratification tool will be established with an analysis of morphological and functional imaging, based on the use of MET-RADS criteria. So, in conclusion, RADIOSA aims to define the optimal management of bone/nodal PCa relapses in a SBRT regimen. This study will increase our knowledge on low-burden metastatic PCa in the era of high precision and high technology personalized medicine, offering highly effective therapy in terms of clinical outcome and cost-effectiveness. TRIAL REGISTRATION: The RADIOSA study was prospectively registered at clinicaltrials.gov ( NCT03940235 , May 2019).

Incidence of fatigue and low-dose corticosteroid use in prostate cancer patients receiving systemic treatment: a meta-analysis of randomized controlled trials.

BACKGROUND: Cancer-related fatigue (CRF) is a complex condition that is reported in > 50% of cancer patients. In men with castration-resistant prostate cancer (CRPC), CRF was reported in 12-21% of patients. Approved systemic therapy against CRPC is commonly administered in combination with androgen-deprivation treatment (ADT) and, in some cases, with daily, low-dose corticosteroids. Importantly, the use of low-dose corticosteroids is associated with multiple negative effects, including reduced muscle mass. On these grounds, we hypothesized that the chronic use of corticosteroids may increase the incidence of fatigue in patients with prostate cancer. METHODS: We reviewed all randomized trials published during the last 15 years conducted in patients with prostate cancer receiving systemic treatment and we performed a sub-group analysis to gather insights regarding the potential differences in the incidence of fatigue in patients receiving vs. not receiving daily corticosteroids as part of their systemic anti-neoplastic regimen. RESULTS: Overall, 22,734 men enrolled in prospective randomized phase II and III trials were evaluable for fatigue. Estimated pooled incidence of grade 1-2 fatigue was 30.89% (95% CI = 25.34-36.74), while estimated pooled incidence of grade 3-4 fatigue was reported in 3.90% (95% CI = 2.91-5.02). Sub-group analysis showed that grade 3-4 fatigue was approximately double in patients who received daily corticosteroids as part of their anti-neoplastic treatment (5.58; 95% CI = 4.33-6.98) vs. those who did not (2.67%; 95% CI = 1.53-4.11). CONCLUSION: Our findings highlight the need for ad hoc-designed prospective clinical trials to investigate whether the benefits associated with low-dose, daily corticosteroids outweigh the risks associated with corticosteroid-related adverse events such as fatigue.

Neutrophil, Platelets, and Eosinophil to Lymphocyte Ratios Predict Gleason Score Upgrading in Low-Risk Prostate Cancer Patients.

BACKGROUND: Several biochemical and clinical markers have been proposed for selecting patients for active surveillance (AS). However, some of these are expensive and not easily accessible. Moreover, currently about 30% of patients on AS harbor aggressive disease. Hence, there is an urgent need for other tools to accurately identify patients with low-risk prostate cancer (PCa). PATIENTS: We retrospectively reviewed the medical records of 260 patients who underwent radical prostatectomy and were eligible for AS according to the following criteria: clinical stage T2a or less, prostate-specific antigen level < 10 ng/mL, 2 or fewer cores involved with cancer, Gleason score (GS) ≤6 grade, and prostate-specific antigen density < 0.2 ng/mL/cc. METHODS: Univariate and multivariate analyses were performed to evaluate the association of patient and tumor characteristics with reclassification, defined as upstaged (pathological stage >pT2) and upgraded (GS ≥7) disease. A base model (age, prostate-specific antigen, prostate volume, and clinical stage) was compared with models considering neutrophil to lymphocyte ratio (NLR) or platelets to lymphocyte ratio (PLR), monocyte to lymphocyte (MLR), and eosinophil to lymphocyte ratio (ELR). OR and 95% CI were calculated. Finally, a decision curve analysis was performed. RESULTS: Univariate and multivariate analyses showed that NLR, PLR, and ELR upgrading were significantly associated with upgrading (ORs ranging from 2.13 to 4.13), but not with upstaging except for MLR in multivariate analysis, showing a protective effect. CONCLUSION: Our results showed that NLR, PLR, and ELR are predictors of Gleason upgrading. Therefore, these inexpensive and easily available tests might be useful in the assessment of low-risk PCa, when considering patients for AS.

Robot assisted radical prostatectomy in kidney transplant recipients: surgical, oncological and functional outcomes of two different robotic approaches.

BACKGROUND: To date, few series on robot-assisted radical prostatectomy (RARP) in kidney transplant recipients (KTRs) have been published. PURPOSE: To report the experience of two referral centers adopting two different RARP approaches in KTRs. Surgical, oncological and functional results were primary outcomes evaluated in the study. MATERIAL AND METHODS: We retrospectively analyzed data from 9 KTRs who underwent transperitoneal RARP or Retzius-sparing RARP for PCa from October 2012 to April 2016. Data were reported as median and interquartile range (IQR). Pre- and postoperative outcomes were compared by non-parametric Wilcoxon signed-rank test. Significant differences were accepted when p ≤ 0.05. Overall survival was assessed using Kaplan-Meier method. RESULTS: Four KTRs underwent a T-RARP and 5 a RS-RARP. Patient median age was 60 (56-63) years. Charlson comorbidity index was 6 (5-6). Preoperative median PSA was 5.6 (5-15) ng / mL. Preoperative Gleason score (GS) was 6 in 5 patients, 7 (3 + 4) in 3, and 8 (4 + 4) in one. Pre- and postoperative creatinine were 1.17 (1.1; 1.4) and 1.3 (1.07; 1.57) mg / dL (p = 0.237), while eGFR was 66 (60-82) and 62 (54-81) mL / min / 1.73m2 (p = 0.553), respectively. One (11.1%) Clavien-Dindo grade II complication occurred. Two extended template lymphadenectomies were performed, both with nodal invasion. These two patients experienced a biochemical recurrence and were subjected to RT. Two patients (22.2%) had PSMs. Median follow-up was 42 months. Seven patients (77.8%) were continent, 5 (55.6%) were potent. Two (22.2%) patients died during follow-up for oncologic unrelated causes. CONCLUSIONS: Our series suggests that both RARP approaches are safe and feasible techniques in KTRs for PCa.

Multiparametric Magnetic-Resonance to Confirm Eligibility to an Active Surveillance Program for Low-Risk Prostate Cancer: Intermediate Time Results of a Third Referral High Volume Centre Active Surveillance Protocol.

BACKGROUND: To evaluate the role of confirmatory multiparametric magnetic resonance imaging (mpMRI) of the prostate at the time of Active Surveillance (AS) enrollment to reduce disease misclassification. MATERIALS: From 2012 to 2016, 383 patients with low-risk disease respecting Prostate Cancer Research International AS criteria underwent confirmatory 1.5-T mpMRI. AS was proposed to patients with Prostate Imaging and Report and Data System (PI-RADS) score ≤3 and no extraprostatic extension (EPE), whereas patients with PI-RADS score ≥4 and/or EPE were treated actively. Kaplan-Meier analyses quantified progression-free survival (PFS) in patients enrolled in the AS program. Logistic regression analyses tested the association between confirmatory mpMRI and clinically significant prostate cancer (csPCa) at radical prostatectomy (RP). Diagnostic performance of mpMRI was calculated in patients submitted to immediate RP. RESULTS: PFS rate was 99, 90 and 86% at 1, 2 and 3 years respectively. At multivariable analysis, PI-RADS 3, PI-RADS 4, PI-RADS 5 and EPE increased the probability of having csPCa at immediate RP (PI-RADS 3 [OR] 1.2, p = 0.26; PI-RADS 4 [OR] 5.1, p = 0.02; PI-RADS 5 [OR] 6.7; p = 0.009; EPE [OR] 11.8, p < 0.001). Confirmatory mpMRI showed sensibility, specificity, positive predictive value and negative predictive value of 85, 55, 68 and 76% respectively. CONCLUSIONS: MpMRI at the time of AS enrollment reduces the misclassification rate of csPCa. We suggest to perform target biopsies in patients with PI-RADS score 3 and 4 lesions.

Advanced Age Impacts Survival After Radical Nephroureterectomy for Upper Tract Urothelial Carcinoma.

INTRODUCTION: Upper tract urothelial carcinoma is rare but has a poor prognosis. Prognostic factors have been extensively studied in order to provide the best possible management for patients. We have aimed to investigate commonly available factors predictive of recurrence and survival in this patient population at high risk of death and recurrence, with an emphasis on the effects of age (using a cutoff of 70 years) on survival outcomes. PATIENTS AND METHODS: From 1387 patients with clinically nonmetastatic upper tract urothelial carcinoma treated with radical nephroureterectomy at 21 academic hospital centers between 2005 and 2021, 776 patients were eligible and included in the study. Univariable and multivariable Cox regression models were built to evaluate the independent prognosticators for intravesical and extravesical recurrence, overall survival, and cancer-specific survival according to age groups. A P value of <.05 was considered statistically significant. RESULTS: We did not find an association between groups aged <70 and >70 years old and preoperatively clinical or histopathological characteristics. Kaplan-Meier analysis was found no statistical significance between the 2 age groups in terms of intravesical or extravesical recurrence (P = .09 and P = .57). Overall survival (P = .0001) and cancer-specific survival (P = .0001) have been found to be statistically significantly associated with age as independent predictors (confounding factors: gender, tumor size, tumor side, clinical T stage, localization, preoperative hydronephrosis, tumor localization, type of surgery, multifocality of the tumor, pathological grade, lymphovascular invasion, concomitant CIS, lymph node status, necrosis, or history of previous bladder cancer). CONCLUSION: This research confirms that patients aged 70 and above who undergo radical nephroureterectomy may have worse outcomes compared to younger patients, older patients needing an improved care and management of UTUC to improve their outcomes in the setting of an increase in this aged population group.

Time to progression is the main predictor of survival in patients with high-risk nonmuscle invasive bladder cancer: Results from a machine learning-based analysis of a large multi-institutional database.

BACKGROUND: In patients affected by high-risk nonmuscle invasive bladder cancer (HR-NMIBC) progression to muscle invasive status is considered as the main indicator of local treatment failure. We aimed to investigate the effect of progression and time to progression on overall survival (OS) and to investigate their validity as surrogate endpoints. METHODS: A total of 1,510 patients from 18 different institutions treated for T1 high grade NMIBC, followed by a secondary transurethral resection and BCG intravesical instillation. We relied on random survival forest (RSF) to rank covariates based on OS prediction. Cox's regression models were used to quantify the effect of covariates on mortality. RESULTS: During a median follow-up of 49.0 months, 485 (32.1%) patients progressed to MIBC, while 163 (10.8%) patients died. The median time to progression was 82 (95%CI: 78.0-93.0) months. In RSF time-to-progression and age were the most predictive covariates of OS. The survival tree defined 5 groups of risk. In multivariable Cox's regression models accounting for progression status as time-dependent covariate, shorter time to progression (as continuous covariate) was associated with longer OS (HR: 9.0, 95%CI: 3.0-6.7; P < 0.001). Virtually same results after time to progression stratification (time to progression ≥10.5 months as reference). CONCLUSION: Time to progression is the main predictor of OS in patients with high risk NMIBC treated with BCG and might be considered a coprimary endpoint. In addition, models including time to progression could be considered for patients' stratification in clinical practice and at the time of clinical trials design.

Investigating Nutritional and Inflammatory Status as Predictive Biomarkers in Oligoreccurent Prostate Cancer-A RADIOSA Trial Preliminary Analysis.

(1) Background: In the RADIOSA phase II randomized clinical trial (NCT03940235), the biology task entails the identification of predictive and prognostic biomarkers in the context of oligorecurrent, castration-sensitive prostate cancer in order to distinguish polymetastatic from oligometastatic disease. This may lay the groundwork for personalized treatments for those patients who could really benefit from metastasis-directed therapies. (2) Methods: Oligorecurrent PCa pts with three or fewer bone or lymph nodal localizations were randomized 1:1 to receive SBRT alone (arm A) or SBRT + 6 months of ADT (arm B). Common serum-derived biomarkers were collected at baseline, and at 3 months after RT. The prognostic nutritional index, an immune and nutrition-based prognostic score, and the controlling nutritional status (CONUT) score, a scoring system for evaluating patient's nutritional status, were calculated in accordance with the body of available literature. As inflammatory indicators, neutrophil-lymphocyte ratio (NLR) and the NLR-albumin ratio (NLRAR) were assessed. Changes in these parameters between baseline and the 3-month timepoint were evaluated both in absolute and relative values. Changes in these parameters between baseline and the 3-month timepoint were evaluated. Significant differences in the trend of these parameters were assessed using the non-parametric Wilcoxon rank-sum test. A network analysis to analyze the relationships between different features stratifying patients according to the arm of study and site of metastases was performed. (3) Results: The current analysis comprised 88 patients (45 arm A, SBRT only, and 43 arm B, SBRT + ADT). When patients were stratified by ADT administration, cholesterol values showed an increasing trend in the group receiving ADT (p = 0.005) which was no longer significant at 1 year. When patients were stratified by site of metastases (52 lymph nodal, 29 bone localizations), the value of NLR was found to be increased in patients with bone localizations (p < 0.05). In addition, the network analysis showed that BMI and NRI are strongly and directly linked for patients at baseline and that this correlation is no longer found at three months. Finally, when patients were divided according to time from surgery to oligorecurrence (enrollment) the patients with a longer time (>6.7 years) showed an increase in CONUT score from baseline. All the other nutritional and inflammatory scores or parameters investigated in the present analysis showed no statistically significant differences at baseline, three months, 1 year, and in absolute change. (4) Conclusions: The nutritional and inflammatory parameters do not seem to represent valuable candidates for possible use in clinical decision making in our cohort of patients and a reliable biological characterization of the oligometastatic state in prostate cancer still seems far from being achieved. Ongoing molecular analysis will show if there is a role of mutational landscape in the definition of the oligometastatic state.

Predicting Peri-Operative Outcomes in Patients Treated with Percutaneous Thermal Ablation for Small Renal Masses: The SuNS Nephrometry Score.

Our objective was to develop a new, simple, and ablation-specific nephrometry score to predict peri-operative outcomes and to compare its predictive accuracy to PADUA and RENAL scores. Overall, 418 patients were treated with percutaneous thermal ablation (microwave and radiofrequency) between 2008 and 2021. The outcome of interest was trifecta status (achieved vs. not achieved): incomplete ablation or Clavien-Dindo ≥ 3 complications or postoperative estimated glomerular filtration rate decrease ≥ 30%. First, we validated the discrimination ability of the PADUA and RENAL scoring systems. Second, we created and internally validated a novel scoring (SuNS) system, according to multivariable logistic regression models. The predictive accuracy of the model was tested in terms of discrimination and calibration. Overall, 89 (21%) patients did not achieve trifecta. PADUA and RENAL scores showed poor ability to predict trifecta status (c-indexes 0.60 [0.53-0.67] and 0.62 [0.55-0.69], respectively). We, therefore, developed the SuNS model (c-index: 0.74 [0.67-0.79]) based on: (1) contact surface area; (2) nearness to renal sinus or urinary collecting system; (3) tumour diameter. Three complexity classes were created: low (3-4 points; 11% of no trifecta) vs. moderate (5-6 points; 30% of no trifecta) vs. high (7-8 points; 65% of no trifecta) complexity. Limitations include the retrospective and single-institution nature of the study. In conclusion, we developed an immediate, simple, and reproducible ablation-specific nephrometry score (SuNS) that outperformed PADUA and RENAL nephrometry scores in predicting peri-operative outcomes. External validation is required before daily practice implementation.

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review.

Radiomics and artificial intelligence (AI) may increase the differentiation of benign from malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma (RCC), differentiation of oncocytoma from RCC, differentiation of different subtypes of RCC, to predict Fuhrman grade, to predict gene mutation through molecular biomarkers and to predict treatment response in metastatic RCC undergoing immunotherapy. Neural networks analyze imaging data. Statistical, geometrical, textural features derived are giving quantitative data of contour, internal heterogeneity and gray zone features of lesions. A comprehensive literature review was performed, until July 2022. Studies investigating the diagnostic value of radiomics in differentiation of renal lesions, grade prediction, gene alterations, molecular biomarkers and ongoing clinical trials have been analyzed. The application of AI and radiomics could lead to improved sensitivity, specificity, accuracy in detecting and differentiating between renal lesions. Standardization of scanner protocols will improve preoperative differentiation between benign, low-risk cancers and clinically significant renal cancers and holds the premises to enhance the diagnostic ability of imaging tools to characterize renal lesions.

Critical Appraisal of Leibovich 2018 and GRANT Models for Prediction of Cancer-Specific Survival in Non-Metastatic Chromophobe Renal Cell Carcinoma.

Within the Surveillance, Epidemiology, and End Results database (2000-2019), we identified 5522 unilateral surgically treated non-metastatic chromophobe kidney cancer (chRCC) patients. This population was randomly divided into development vs. external validation cohorts. In the development cohort, the original Leibovich 2018 and GRANT categories were applied to predict 5- and 10-year cancer-specific survival (CSS). Subsequently, a novel multivariable nomogram was developed. Accuracy, calibration and decision curve analyses (DCA) tested the Cox regression-based nomogram as well as the Leibovich 2018 and GRANT risk categories in the external validation cohort. The accuracy of the Leibovich 2018 and GRANT models was 0.65 and 0.64 at ten years, respectively. The novel prognostic nomogram had an accuracy of 0.78 at ten years. All models exhibited good calibration. In DCA, Leibovich 2018 outperformed the novel nomogram within selected ranges of threshold probabilities at ten years. Conversely, the novel nomogram outperformed Leibovich 2018 for other values of threshold probabilities. In summary, Leibovich 2018 and GRANT risk categories exhibited borderline low accuracy in predicting CSS in North American non-metastatic chRCC patients. Conversely, the novel nomogram exhibited higher accuracy. However, in DCA, all examined models exhibited limitations within specific threshold probability intervals. In consequence, all three examined models provide individual predictions that might be suboptimal and be affected by limitations determined by the natural history of chRCC, where few deaths occur within ten years from surgery. Further investigations regarding established and novel predictors of CSS and relying on large sample sizes with longer follow-up are needed to better stratify CSS in chRCC.