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INTRODUCTION: Collecting duct, or Bellini duct, renal cell carcinoma (CDRCC) is a rare tumour, comprising only 0.4-2% of all renal cell carcinoma. The goal of this study was to evaluate the cases in our institution and look at current available literature. MATERIAL AND METHODS: We searched all data on renal cell tumours in our institution between 2011 and 2021 and identified four cases with confirmed CDRCC pathology. Important features were listed and analysed. We also reviewed current available literature and compared it to our case series. RESULTS: All cases were men with a median age of 63.5 years. All were symptomatic at presentation. Two patients presented with flank pain and two with gross haematuria. Three patients had stage IV disease at time of presentation and one stage III disease. All cases had clear Bellini duct renal cell carcinoma appearance on microscopy with infiltrative tubular architecture and high-grade nuclear features. Immunohistochemic (IHC) staining was performed for diagnostic confirmation. Three patients underwent radical nephrectomy and received adjuvant chemotherapy. One case had kidney biopsy for diagnostic confirmation and received first line chemotherapy. Immunotherapy or tyrosine kinase inhibitor (TKI) were started for second, third or fourth line of treatment. Median overall survival after diagnosis was 11 months. CONCLUSIONS: CDRCC is a rare subtype of renal cell carcinoma with poor prognosis, typically presenting in a more advanced or metastatic stage. Diagnosis can be challenging. Multimodality treatment should be considered using radical surgery and systemic treatment. ispartof: CENTRAL EUROPEAN JOURNAL OF UROLOGY vol:75 issue:3 pages:252-256 ispartof: location:Poland status: published

BACKGROUND: The possibility of predicting pathologic features before surgery can support clinicians in selecting the best treatment strategy for their patients. We sought to develop and externally validate pretreatment nomograms for the prediction of pathological features from a prospective multicentre series of robotic-assisted laparoscopic prostatectomy (RALP) procedures. DESIGN, SETTING, AND PARTICIPANTS: Between 2009 and 2016, data from 6823 patients undergoing RALP in 25 academic and community hospitals were prospectively collected by the Belgian Cancer Registry. Logistic regression models were applied to predict extraprostatic extension (EPE; pT3a,b-4), seminal vesicle invasion (SVI; pT3b), and high-grade locally advanced disease (HGLA; pT3b-4 and Gleason score [GS] 8-10) using the following preoperative covariates: prostate-specific antigen, clinical T stage, biopsy GS, and percentage of positive biopsy cores. Internal and external validation was performed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The stability of the model was assessed via tenfold cross-validation using 80% of the cohort. The nomograms were independently externally validated using the test cohort. The discriminative accuracy of the nomograms was quantified as the area under the receiver operating characteristic curve and graphically represented using calibration plots. RESULTS AND LIMITATION: The nomograms predicting EPE, SVI, HGLA showed discriminative accuracy of 77%, 82%, and 88%, respectively. Following external validation, the accuracy remained stable. The prediction models showed excellent calibration properties. CONCLUSIONS: We developed and externally validated multi-institutional nomograms to predict pathologic features after RALP. These nomograms can be implemented in the clinical setting or patient selection in clinical trials. PATIENT SUMMARY: We developed novel nomograms using nationwide data to predict postoperative pathologic features and lethal prostate cancer. ispartof: EUROPEAN UROLOGY ONCOLOGY vol:1 issue:4 pages:338-345 ispartof: location:Netherlands status: published