Comparing Patient's Confidence in Clinical Capabilities in Urology: Large Language Models Versus Urologists.

Background And Objective: Data on interaction of patients with artificial intelligence (AI) are limited, primarily derived from small-scale studies, cross-sectional surveys, and qualitative reviews. Most patients have not yet encountered AI in their clinical experience. This study explored patients' confidence in AI, specifically large language models, after a direct interaction with a chatbot in a clinical setting.

Large language model use in clinical oncology.

Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, and the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, and compare methodological approaches and outcomes.

Impact of a kidney-adjusted ERAS protocol on postoperative outcomes in patients undergoing partial nephrectomy.

Purpose: Evaluation of a kidney-adjusted enhanced recovery after surgery (ERAS) protocol (kERAS) in patients undergoing nephron-sparing surgery (PN).

Methods: The kERAS protocol is a multidimensional protocol focusing on optimized perioperative fluid and nutrition management as well as strict intraoperative and postoperative blood pressure limits. It was applied in a prospective cohort (n = 147) of patients undergoing open or robotic PN.

Tranexamic acid reduces perioperative blood transfusions following open radical cystectomy - a propensity-score matched analysis.

Purpose: Radical cystectomy is associated with bleeding and high transfusion rates, presenting challenges in patient management. This study investigated the prophylactic use of tranexamic acid during radical cystectomy.

Methods: All consecutive patients treated with radical cystectomy at a tertiary care university center were included from a prospectively maintained database.

[Incidence, therapy, and prognosis of prostate cancer in Baden-Württemberg: analysis based on cancer registry data].

Background: Prostate cancer (PCa) is the most common solid tumor in men in Germany. Collection of epidemiological and clinical data has been centralized for several years due to legal requirements via the state cancer registries. Thus, the reporting of diagnosis, therapy, and progression of cancer is obligatory in Germany.

Maximizing efficiency and ensuring safety: Exploring the outcomes of 2 consecutive open radical cystectomies by the same team within a single surgical day.

Background: The purpose of this study was to evaluate the outcomes of performing 2 consecutive open radical cystectomies (RCs) within 1 day by the same surgical team.

Patients And Methods: A retrospective analysis was conducted on data from patients who underwent RC at a single tertiary care center from January 2015 to February 2023. Patient characteristics, perioperative outcomes and endpoints were analyzed.

Cyclin A2 Expression as Predictive Biomarker in Muscle-Invasive Upper Tract Urothelial Carcinoma.

Introduction: The aim was to evaluate the prognostic value of altered Cyclin A2 (CCNA2) gene expression in upper tract urothelial carcinoma (UTUC) and to assess its predictive potential as a prognostic factor for overall survival (OS) and disease-free survival.

Methods: 62 patients who underwent surgical treatment for UTUC were included. Gene expression of CCNA2, MKI67, and p53 was analyzed by quantitative reverse transcriptase polymerase chain reaction.

Peritoneal Flap for Lymphocele Prophylaxis Following Robotic-assisted Radical Prostatectomy with Lymph Node Dissection: The Randomised Controlled Phase 3 PELYCAN Trial.

Background: Symptomatic lymphoceles (SLCs) after transperitoneal robotic-assisted radical prostatectomy with pelvic lymph node dissection (PLND) are common. Evidence from randomised controlled trials (RCTs) on the impact of peritoneal flaps (PFs) on lymphocele (LC) reduction is inconclusive.

Objective: To show that addition of PFs leads to a reduction of postoperative SLCs.

A self-supervised vision transformer to predict survival from histopathology in renal cell carcinoma.

Purpose: To develop and validate an interpretable deep learning model to predict overall and disease-specific survival (OS/DSS) in clear cell renal cell carcinoma (ccRCC).

Methods: Digitised haematoxylin and eosin-stained slides from The Cancer Genome Atlas were used as a training set for a vision transformer (ViT) to extract image features with a self-supervised model called DINO (self-distillation with no labels). Extracted features were used in Cox regression models to prognosticate OS and DSS.

Integrin Expression in Localized Prostate Cancer: A TCGA and MSKCC Cohort-based Exploratory Analysis.

Background/aim: Diagnostic and prognostic biomarkers in localized prostate cancer (PC) are insufficient. Treatment stratification relies on prostate-specific antigen, clinical tumor staging and International Society of Urological Pathology (ISUP) grading, whereas molecular profiling remains unused. Integrins (ITG) have an important function in bidirectional signaling and are associated with progression, proliferation, perineural invasion, angiogenesis, metastasis, neuroendocrine differentiation, and a more aggressive disease phenotype in PC.

Changes in neutrophile-to-lymphocyte ratio as predictive and prognostic biomarker in metastatic prostate cancer treated with taxane-based chemotherapy.

Objectives: To assess the predictive and prognostic value of changes in longitudinal neutrophile-to-lymphocyte (NLR) ratios in men receiving taxane-based chemotherapy for metastatic prostate cancer (PC).

Methods: Retrospective, unicentric cohort study of patients treated with either docetaxel for metastatic hormone-sensitive PC (mHSPC) or docetaxel or cabazitaxel for metastatic castration-refractory PC (mCRPC) at a tertiary referral hospital between 2010 and 2019. NLR ratios were calculated for each cycle.

Prospective, Randomized Comparative Evaluation of a Novel Hands-On Endourology Training Curriculum.

Introduction: The aim of this randomised prospective trial was to evaluate a novel hands-on endourological training programme (HTP) and compare it to the standard endourological colloquium (SC).

Methods: A new HTP was created based on a sequence of theoretical, video-based, and practical elements emphasising contemporary teaching methods. An existing SC in which live endourological operations were attended served as a comparison.

Artificial intelligence for renal cancer: From imaging to histology and beyond.

Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging.

Deep learning can predict survival directly from histology in clear cell renal cell carcinoma.

For clear cell renal cell carcinoma (ccRCC) risk-dependent diagnostic and therapeutic algorithms are routinely implemented in clinical practice. Artificial intelligence-based image analysis has the potential to improve outcome prediction and thereby risk stratification. Thus, we investigated whether a convolutional neural network (CNN) can extract relevant image features from a representative hematoxylin and eosin-stained slide to predict 5-year overall survival (5y-OS) in ccRCC.

Systemic inflammatory biomarkers as predictive and prognostic factors in men with metastatic castration-refractory prostate cancer treated with docetaxel therapy: a comprehensive analysis in a German real-world cohort.

Purpose: Advances in therapy of metastatic castration-refractory prostate cancer (mCRPC) resulted in more therapeutic options and led to a higher need of predictive/prognostic biomarkers. Systemic inflammatory biomarkers could provide the basis for personalized treatment selection. This study aimed to assess the modified Glasgow Prognostic Score (mGPS), the neutrophile-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR) and the systemic immune-inflammation index (SII) in men with mCRPC under docetaxel.

Comorbidity Scores and Machine Learning Methods Can Improve Risk Assessment in Radical Cystectomy for Bladder Cancer.

Background: Pre-operative risk assessment in radical cystectomy (RC) is an ongoing challenge especially in elderly patients.

Objective: To evaluate the ability of comorbidity indices and their combination with clinical parameters in machine learning models to predict mortality and morbidity after RC.

Methods: In 392 patients who underwent open RC, complication and mortality rates were reported.

Baseline Modified Glasgow Prognostic Score (mGPS) Predicts Radiologic Response and Overall Survival in Metastatic Hormone-sensitive Prostate Cancer Treated With Docetaxel Chemotherapy.

Background/aim: To assess the baseline inflammatory markers modified Glasgow Prognostic Score (mGPS), systemic immune-inflammation index (SII), and neutrophile-to-lymphocyte ratio (NLR) as pragmatic tools for predicting response to chemohormonal therapy (docetaxel plus ADT) and prognosis in men with metastatic hormone-sensitive prostate cancer (mHSPC).

Patients And Methods: Male patients who received docetaxel at a tertiary university care center between 2014 and 2019 were screened for completion of 6 cycles. NLR, SII, mGPS, overall survival (OS), three-year survival, and radiologic response were assessed.

Artificial intelligence to predict oncological outcome directly from hematoxylin and eosin-stained slides in urology.

Introduction: Artificial intelligence (AI) has been successfully applied for automatic tumor detection and grading in histopathological image analysis in urologic oncology. The aim of this review was to assess the applicability of these approaches in image-based oncological outcome prediction.

Evidence Acquisition: A systematic literature search was conducted using the databases MEDLINE through PubMed and Web of Science up to April 20, 2021.

Patient Compliance in Assessing Electronic Patient-Reported Outcome Measures after Urologic Surgery.

Introduction: This study aimed to assess patient compliance with a newly established electronic patient-reported outcome measure (ePROM) system after urologic surgery and to identify influencing factors.

Methods: Digital surveys were provided to patients undergoing cystectomy, radical or partial nephrectomy, or transurethral resection of bladder tumor via a newly established ePROM system. Participants received a baseline survey preoperatively and several follow-up surveys postoperatively.

Onset and burden of lower limb lymphedema after radical prostatectomy: a cross-sectional study.

Objectives: To explore men's onset and burden of lower limb lymphedema (LLL) after radical prostatectomy (RP) with pelvic lymph node dissection (PLND).

Patients And Methods: A cross-sectional survey-based study was conducted nation-wide and web-based in Germany. Part 1 included 15 multidisciplinary compiled questions with three questions from the Short Form 12 Health Survey (SF-12) and the WHO activity recommendation and part 2 included the validated German Lymph-ICF-Questionnaire (Lymph-ICF-LL).

High IL-22RA1 gene expression is associated with poor outcome in muscle invasive bladder cancer.

Background: The cell surface interleukin 22 (IL-22) receptor complex is mainly expressed in epithelial and tissue cells like pancreatitis cells. Recent studies described that IL-22R was overexpressed in malignant diseases and was associated with a poor overall survival (OS). The role of IL-22RA1 gene expression in muscle invasive bladder cancer (MIBC) has not been investigated, yet.

Validation of a German translation of the CARE questionnaire and its implementation as electronic PROM to assess patient-reported postoperative convalescence and recovery after major urological surgery.

Purpose: To validate a German translation of the convalescence and recovery evaluation (CARE) as an electronic patient-reported outcome measure (ePROM) and use it to assess recovery after major urological surgery.

Methods: The CARE questionnaire was provided to patients scheduled for major urological surgery preoperatively, at discharge and 6 weeks postoperatively, using an ePROM system. Cronbach's alpha, inter-scale correlations and confirmatory factor analysis (CFA) were used to validate the translation.

Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer.

Objective: To develop a new digital biomarker based on the analysis of primary tumour tissue by a convolutional neural network (CNN) to predict lymph node metastasis (LNM) in a cohort matched for already established risk factors.

Patients And Methods: Haematoxylin and eosin (H&E) stained primary tumour slides from 218 patients (102 N+; 116 N0), matched for Gleason score, tumour size, venous invasion, perineural invasion and age, who underwent radical prostatectomy were selected to train a CNN and evaluate its ability to predict LN status.

Results: With 10 models trained with the same data, a mean area under the receiver operating characteristic curve (AUROC) of 0.

Partial nephrectomy preserves renal function without increasing the risk of complications compared with radical nephrectomy for renal cell carcinomas of stages pT2-3a.

Objectives: To compare the operative and functional result of partial and radical nephrectomy in renal cell carcinomas of stages pT2-3a.

Methods: Consecutive patients with renal cell carcinoma of stages pT2-3a, cN0 and cM0, who underwent partial or radical nephrectomy between January 2005 and October 2019 at a tertiary care center were included. Data were collected retrospectively.

Nephrometry Scores: The Effect of Imaging on Routine Read-out and Prediction of Outcome of Nephron-sparing Surgery.

Background/aim: This study investigated the impact of available preoperative imaging on the reliability and predictive accuracy of RENAL and PADUA nephrometry-scoring systems for renal tumors.

Patients And Methods: Five urologists determined RENAL and PADUA scores using preoperative imaging data (computed tomography and magnetic resonance imaging) of 100 patients admitted for partial nephrectomy with the following combinations: T0: transverse planes without excretory phase (EP), TC0: transverse and coronal planes without EP, TC1: transverse and coronal planes with EP. Reference standard was obtained by a uro-radiologist.