The currently available EORTC, CUETO and EAU2021 risk stratifications were originally developed to predict recurrence and progression in non-muscle-invasive bladder cancer (NMIBC). However, they have not been validated to differentiate between high-grade (HG) and low-grade (LG) recurrence-free survival (RFS), which are distinct events with specific implications. We aimed to evaluate the accuracy of available risk models and identify additional risk factors for HG RFS and PFS among NMIBC patients treated with Bacillus Calmette–Guérin (BCG). We retrospectively included 171 patients who underwent transurethral resection of the bladder tumor (TURBT), of whom 73 patients (42.7%) experienced recurrence and 29 (17%) developed progression. Initially, there were 21 low-grade and 52 high-grade recurrences. EORTC2006, EORTC2016 and CUETO recurrence scoring systems lacked accuracy in the prediction of HG RFS (C-index 0.63/0.55/0.59, respectively). EAU2021 risk stratification, EORTC2006, EORTC2016, and CUETO progression scoring systems demonstrated low to moderate accuracy (C-index 0.59/0.68/0.65/0.65) in the prediction of PFS. In the multivariable analysis, T1HG at repeat TURBT (HR = 3.17 p < 0.01), tumor multiplicity (HR = 2.07 p < 0.05), previous history of HG NMIBC (HR = 2.37 p = 0.06) and EORTC2006 progression risk score (HR = 1.1 p < 0.01) were independent predictors for HG RFS. To conclude, available risk models lack accuracy in predicting HG RFS and PFS in -NMIBC patients treated with BCG.

Up-to-date studies emphasize the role of human urinary and intestinal microbiome in maintaining urogenital health. Both microbial flora and sexually transmitted pathogens may affect metabolic or immune mechanisms and consequently promote or inhibit prostate carcinogenesis. Hereby, we review the most current evidence regarding the microbial factors and their link to prostate cancer. We conducted a literature search up to December 2020. The microbial impact on prostate cancer initiation and progression is complex. The proposed mechanisms of action include induction of chronic inflammatory microenvironment (Propionibacterium spp., sexually-transmitted pathogens) and direct dysregulation of cell cycle (Helicobacter pylori, Kaposi’s sarcoma-associated herpesvirus- KSHV, human papilloma virus 18- HPV18). Suppression of immune cell expression and downregulating immune-associated genes are also observed (Gardnerella vaginalis). Additionally, the impact of the gut microbiome proved relevant in promoting tumorigenesis (Bacteroides massiliensis). Nevertheless, certain microbes appear to possess anti-tumor properties (Listeria monocytogenes, Pseudomonas spp.), such as triggering a robust immune response and apoptotic cancer cell death. The role of microbial factors in prostate cancer development is an emerging field that merits further studies. In the future, translating microbial research into clinical action may prove helpful in predicting diagnosis and potential outcomes of the disease.

The aim of our study was to determine the clinical utility of neutrophil-to-lymphocyte ratio (NLR) in predicting presence and prognosis of nodal involvement in patients treated with radical prostatectomy (RP) due to prostate cancer. This single-centre retrospective study included 205 patients treated with RP and lymphadenectomy between 2012 and 2018. Logistic regression and Kaplan–Meier analyses were performed to evaluate the prognostic value of preoperative NLR in terms of nodal spread and survival. Patients staged pN1 presented lower mean NLR (2.53 vs 3.86; p = 0.0025) compared to pN0 patients. On multivariable analysis of different haematological markers, only NLR exceeding the median (≥ 2.7) predicted pN1 (OR = 0.38; p = 0.0367) independently of biopsy grading and PSA. In internal validation (n = 31 pN1, n = 174 pN0) on the bootstrapped dataset using a spare cutoff of NLR ≥ 4.1 would allow sparing lymphadenectomy in 22.09% pN0 patients, missing 6.45% pN1 (NPV 92.66%; 95% CI 84.91–100%). Noticeably, in pN1 patients NLR ≥ 2.7 correlated with shorter overall survival (p = 0.0196), despite its association with reduced risk of pN1. High pre-prostatectomy NLR was negatively associated with pN1, yielding high NPV in internal validation. Simultaneously, high NLR in pN1 patients was associated with shorter survival.

Purpose: To evaluate the outcomes of high-grade T1 non-muscle-invasive bladder cancer treatment (NMIBC) in elderly patients over 80 years of age. Methods: This is a retrospective single tertiary-centre study. Medical records of patients with T1 high-grade NMIBC treated with transurethral resection of the bladder tumour (TURBT) were reviewed. Among 269 patients with high-grade T1 NMIBC, 74 individuals were over 80 years of age at the time of surgery. Finally, 67 patients met the inclusion criteria. Results: Only 47.8% of patients (N = 32) received at least five of the six instillations of the BCG immunotherapy induction course. Oncological outcomes were compared between patients who received at least the induction course of BCG and non-BCG-treated patients matched to each other based on age and Charlson comorbidity index. Thirty case–control pairs were included in the final analysis. Rates of disease recurrence (80% vs. 53%) and cancer-specific mortality (40% vs. 10%) were significantly higher in the group of patients who did not receive BCG. BCG therapy, Charlson comorbidity index, haemoglobin concentration and the number of tumours > 3 in TURBT constituted independent prognostic factors for cancer-specific survival (CSS). Conclusion: BCG should be strongly recommended to patients with T1HG NMIBC despite advanced age and comorbidities. Already BCG induction improves CSS and reduces the recurrence rate in octogenarians with T1HG bladder cancer.

Purpose: Our study aimed to develop a noninvasive model using a combination of the set of clinical data and uroflowmetry (UFL) to differentiate between detrusor underactivity (DU) and bladder outlet obstruction (BOO) in non-neurogenic male patients with lower urinary tract symptoms (LUTS). Methods: Data from 229 men with LUTS, diagnosed with DU or BOO on a pressure-flow study (PFS), were retrospectively analyzed, including medical history, Core Lower Urinary Tract Symptoms score (CLSS) questionnaire, UFL and PFS. Uni- and multivariate logistic regression were utilized for the prediction analyses. Results: Of the cohort, 128 (55.9%) patients were diagnosed with DU. A multivariate logistic regression analysis identified less prevalent nocturia (OR 0.27, p < 0.002), more prevalent intermittency (OR 2.33, p = 0.03), less prevalent weak stream (OR 0.14, p = 0.0004), lower straining points in CLSS (OR 0.67, p = 0.02), higher slow stream points in CLSS (OR 1.81, p = 0.002), higher incomplete emptying points in CLSS (OR 1.31, p < 0.02), lower PVR ratio (OR 0.20, p = 0.03), and present features of fluctuating (OR 2.00, p = 0.05), fluctuating-intermittent (OR 3.09, p < 0.006), and intermittent (OR 8.11, p = 0.076) UFL curve shapes as independent predictors of DU. The above prediction model demonstrated satisfactory accuracy (c-index of 0.783). Conclusion: Our 10-factor model provides a noninvasive approach to differentiate DU from BOO in male patients with non-neurogenic LUTS, offering a valuable alternative to invasive PFS.

Background: To evaluate and synthesize existing evidence on non-invasive methods for diagnosing detrusor underactivity (DU) in men presenting with lower urinary tract symptoms (LUTS), focusing on their feasibility and diagnostic accuracy. Methods: A systematic search of PubMed, Scopus, and Web of Science databases was conducted for original articles reporting on non-invasive diagnostic tests for DU in men with LUTS. Data extraction focuses on study characteristics, diagnostic methods, and accuracy. The risk of bias was assessed using the QUADAS-2 tool. Results: Eighteen studies involving 7390 patients, of whom 3194 were diagnosed with DU, were included in our analysis. The evaluated diagnostic methods included ultrasound parameters, biomarkers, uroflowmetry results, symptom questionnaires, and clinical characteristics. Developed models, including those based on artificial intelligence (AI), and nomograms were also assessed. The symptom questionnaire DUA-SQ showed the highest sensitivity of 95.8%, while ultrasound measurements, such as detrusor wall thickness showed 100% specificity but limited sensitivity (42%). Models incorporating clinical variables achieved sensitivity rates of over 75%. Uroflowmetry parameters, particularly presence of "sawtooth" and "interrupted" waveforms, demonstrated sensitivity of 80% and specificity of 87%. Biomarkers, including serum adiponectin and urine NO/ATP ratio, achieved sensitivity of 79% and 88.5%, respectively. AI models showed potential, with sensitivities ranging from 65.9% to 79.7%. Due to the poor quality of the studies and data heterogeneity, meta-analysis was not performed. Conclusions: Non-invasive diagnostic methods for DU, particularly DUA-SQ, ultrasound measurements, and AI models, demonstrate potential, though their accuracies vary. Further research is needed to standardize these methods and enhance their diagnostic reliability. Trial registration: The study protocol was registered with PROSPERO (CRD42024556425). Clinical trial number: not applicable.