Abstract Introduction Accurate preoperative prediction of lymph node invasion (LNI) is crucial for deciding on extended pelvic lymph node dissection (ePLND) in radical prostatectomy. Traditional nomograms such as Briganti, Partin, and MSKCC are widely used, but machine learning (ML)–based models may improve predictive accuracy. Materials and methods Data from 471 prostate cancer patients were analyzed, including demographic, clinical, and histopathological variables and scores from Briganti, Partin, and MSKCC nomograms. Eleven ML algorithms were evaluated, with performance assessed by AUC-ROC, accuracy, sensitivity, specificity, and F1-score. Class imbalance was addressed with resampling techniques, and feature importance analyses were performed. Results LNI was present in 97 patients (20.6%). Significant predictors included MSKCC and Partin scores, PSA, ISUP grade, PIRADS score, lymphovascular invasion, and age. Neural Network (AUC: 0.81) and Random Forest (AUC: 0.77) showed similar performance to the nomograms (MSKCC: 0.79; Briganti: 0.77; Partin: 0.78) when considering the AUC values and their 95% confidence intervals.Decision tree analysis highlighted negative core count, ISUP grade, prostate density, PSA, BMI, and age as key variables. Combining nomogram scores with ML models resulted in numerically slightly higher AUC values; however, these differences remained within a similar performance range and did not indicate a clinically meaningful improvement. Conclusion Although the AUC values of the ML models appear numerically comparable to, or slightly higher than, those of traditional nomograms, the inherent limitations of the study preclude demonstrating a clinically superior or reliably advantageous performance; therefore, multicenter prospective validation studies are warranted.

BACKGROUND:Pediatric urolithiasis is an increasingly important health concern, and affected children and their families require information that is both accurate and easily understandable. Artificial intelligence (AI)-powered chatbots have become widely used sources of health information; however, the readability, quality, and reliability of their outputs remain insufficiently evaluated. This study aimed to assess the effectiveness and reliability of AI chatbots in providing patient-oriented information on pediatric kidney stone disease and to identify factors influencing the quality and readability of their responses. METHODS:Four AI chatbots (ChatGPT-5, Google Gemini, Claude 3 Opus, and DeepSEEK) were queried with 30 standardized questions related to pediatric kidney stones. Readability was evaluated using the Average Reading Level Consensus (ARLC), Automated Readability Index (ARI), and Simple Measure of Gobbledygook (SMOG). Response quality and reliability were asssessed using the Ensuring Quality Information for Patients (EQIP) tool and Modified DISCERN score. Statistical analyses included one-way analysis of variance ANOVA, Kruskal-Wallis tests, and appropriate post hoc comparisons. RESULTS:Readability differed significantly among the chatbots. Google Gemini demonstrated the highest reading levels across all metrics (ARLC: 14.93, ARI: 16.2, and SMOG: 13.32), whereas ChatGPT, Claude, and DeepSEEK produced less complex test (p < 0.001; large effect sizes, η2 = 0.195-0.512). EQIP scores did not differ significantly between models (p = 0.491, ε2 = 0.021, negligible effect), indicating comparable informational quality. In contrast, reliability varied significantly: ChatGPT and Google Gemini achieved higher Modified DISCERN scores (median 4.00) than Claude and DeepSEEK (median 3.00; p = 0.001, ε2 = 0.318, large effect). Subgroup analyses by question category revealed notable differences in performance, highlighting model-specific strenghts and limitations. CONCLUSIONS:Substantial variability exists in the readability and reliability of AI-generated health information on pediatric urolithiasis. Although ChatGPT and Google Gemini provided more reliable information, Google Gemini's responses were consistently more complex and less accessible. These findings emphasize the need for careful validation and language simplification of AI-generated content before its use in patient and caregiver education.

Background: Testicular germ cell tumors (TGCTs) are the most common solid malignancies in young men. In real-world clinical practice, non-random treatment allocation may result in confounding by indication, as patients with a greater disease burden are more likely to receive chemotherapy. We evaluated the association between treatment strategy and recurrence-free survival using propensity score-based inverse probability of treatment weighting (IPTW). Methods: We retrospectively analyzed 114 patients who underwent radical orchiectomy for TGCT between 2015 and 2024. Patients were classified into active surveillance and chemotherapy groups. Stabilized IPTW was used to balance baseline clinicopathological characteristics. Recurrence-free survival was evaluated using Kaplan-Meier analysis and Cox proportional hazards regression. Residual post-weighting imbalance was addressed by additional covariate adjustment. Results: During follow-up, 29 of 114 patients (25.4%) experienced recurrence. Unadjusted Kaplan-Meier analysis demonstrated no statistically significant difference in recurrence-free survival between treatment groups (log-rank p = 0.150). Consistently, the unadjusted Cox proportional hazards model showed no statistically significant association between treatment strategy and recurrence-free survival (HR = 1.85, 95% CI 0.79-4.34; p = 0.158). After IPTW, treatment strategy remained not significantly associated with recurrence-free survival (HR = 0.96, 95% CI 0.43-2.13; p = 0.911). Additional adjustment for residual post-weighting imbalance yielded similar results (HR = 0.94, 95% CI 0.43-2.03; p = 0.876). Conclusions: After adjustment for measured baseline differences using IPTW, treatment strategy was not statistically significantly associated with recurrence-free survival. Given the limited number of recurrence events, wide confidence intervals, residual covariate imbalance, incomplete propensity-score overlap, and evidence of non-proportional hazards, these findings should be considered exploratory and should not be interpreted as evidence of equivalence.

Aim: To create a multivariate prediction model based on machine learning to find predictors of recurrence after Anderson-Hynes dismembered pyeloplasty Methods: Patients younger than 15 who underwent primary open Anderson-Hynes Dismembered Pyeloplasty between 2011 and 2020 were evaluated. Logistic regression, support vector machine, and random forest were used to train a classifier for predicting recurrence, and the feature importance analysis methods were performed to understand which predictors have more weight in the models. Results: Of the patients, 134 were boys, and 43 were girls, with a mean age of 30.4 (1-168) months. Recurrence developed in 15/177 (8.49%) of the patients. Postoperative anteroposterior renal pelvis diameter and intraoperative urine aspiration volume were the strongest predictors of recurrence. The Random Forest model achieved the best accuracy (AUC = 0.94) in predicting recurrence in patients under 15. Conclusion. To our knowledge, this is the first study to investigate whether the amount of urine aspirated from the intraoperative renal pelvis is predictive of recurrence. We found that the probability of recurrence of ureteropelvic junction obstruction increased as the amount of urine aspirated from the Intraoperative renal pelvis increased.

Introduction: Iatrogenic ureteral injuries following ureterorenoscopic (URS) stone surgery are significant complications that can occur despite the preserved structure of the urinary tract. This study aimed to evaluate the demographic characteristics, types of injuries, timing of diagnosis, and outcomes of treatment methods in patients with iatrogenic ureteral injury after URS. Materials and Methods: Patients with iatorogenic ureteral injury during URS were included based on retrospective data collected from 19 centers across Turkey between November 2010 and December 2022. Demographics, location, and grade of injury, time of diagnosis, and success rates of endourological or reconstructive surgical interventions were analyzed. Surgical success was defined as the absence of postoperative complications and no need for further surgical intervention. Results: Of the 105 patients, 65 were males and 40 females, with a median age of 48 years (20-86). Injuries occurred in the distal ureter in %60, mid-ureter in %18.1, and proximal ureter in %21.9 of cases. Laceration accounted for %64.7 of the injuries, whereas %35.3 occurred during laser use. Diagnosis was made intraoperatively in %21 and postoperatively in %79 of patients, with a median time to postoperative diagnosis of 30 days (1-720). Higher body mass index was associated with lower primary surgical success (p = 0.049). The most common initial treatment was ureteral stent placement. Reconstructive surgeries had lower rates of secondary interventions or complications compared to endourological procedures (p = 0.045). Among patients necessitating a second surgery, those who underwent reconstructive surgery had significantly lower tertiary intervention or complication rates (p < 0.001). Nephrectomy was required in six patients because of renal atrophy. Conclusion: Early diagnosis is crucial in iatrogenic ureteral injuries after URS. Elevated BMI may negatively affect surgical outcomes. Although endourological approaches are commonly used initially, reconstructive surgeries offer more durable outcomes, especially in severe injuries or failed primary treatments, underscoring the need for individualized management strategies.

OBJECTIVE:The aim of this study is to evaluate the effectiveness of sacral neuromodulation (SNM) on clinical symptoms, lower urinary tract function, and objective measurements in patients diagnosed with overactive bladder (OAB) and chronic nonobstructive urinary retention (CNOUR), and to identify factors affecting treatment response. MATERIALS AND METHODS:This multicenter retrospective chart review included patients diagnosed with OAB and CNOUR who underwent SNM between 2015 and 2025 at four tertiary referral centers. All patients underwent a standard two-stage SNM protocol. Clinical evaluation was performed at the first and third postoperative months after stage II implantation using urinary incontinence status, clean intermittent catheterization (CIC) requirement, bladder diary data, and uroflowmetric parameters. Demographic and technical factors affecting success were analyzed. RESULTS:A total of 160 patients were included in the study. Of these patients, 113 (70.6%) were female, and the mean age was 41 years. SNM was performed for OAB in 63 patients (39.4%) and for CNOUR in 97 patients (60.6%). After the first stage of SNM, clinical success was achieved in 50 patients (79.4%) in the OAB group and 68 patients (70.1%) in the CNOUR group. In the CNOUR group, the need for CIC completely disappeared in 38.2% of patients after SNM, while the frequency of catheterization decreased by at least 50% in 22.1% of patients. Urinary incontinence completely resolved in 52% of the OAB group and 69.1% of the CNOUR group. In uroflowmetric evaluation, Qmax and PVR improved significantly in the CNOUR group, whereas voided volume was used as a supportive parameter for interpreting Qmax. A higher number of contacts receiving stimulation during the first stage was significantly associated with treatment success. No serious perioperative complications were observed. CONCLUSION:Sacral neuromodulation is an effective and safe treatment option for patients with overactive bladder and chronic urinary retention. Its ability to reduce the need for catheterization and improve voiding function is of great clinical importance, especially in patients with chronic urinary retention. The success of SNM can be increased with appropriate patient selection, careful evaluation during the testing phase, and optimal technical application.

Erectile dysfunction (ED) represents a significant health concern that affects not only physical well-being but also psychological health and quality of life. This study aimed to investigate the potential of digital biomarkers derived from smartwatches for the risk assessment of ED. This prospective, comparative cross-sectional study investigated digital biomarkers derived from smartwatch technology for ED assessment in 74 male participants (38 ED patients, 36 controls) between May and September 2025. Participants wore iOS-based smartwatches continuously for 14 days to monitor physiological parameters including heart rate variability (HRV), sleep architecture, and physical activity levels. ED diagnosis was established using the International Index of Erectile Function 5-item form (IIEF-5) with scores ≤ 21 indicating ED. Statistical analyses included univariate/multivariate logistic regression and ROC curve analysis. Compared to controls, the ED group demonstrated significantly lower HRV (32 vs. 38.5 ms, p < 0.001), higher resting heart rate (69 vs. 58 bpm, p < 0.001), increased wake time percentage (p < 0.001), decreased deep sleep duration (20

Overactive bladder (OAB) is a common urological condition affecting millions of people worldwide, significantly reducing their quality of life. Patient compliance and active participation in disease management are critical to achieving successful outcomes. This study aims to understand the potential role of AI-assisted chatbots in educating patients with OAB and their impact on health literacy. We compared responses from four AI chatbots (ChatGPT, DeepSeek, Claude, and Gemini) to 16 standardized questions from the AUA Overactive Bladder Patient Guide. Two board-certified urologists independently evaluated responses using Ensuring Quality Information for Patients (EQIP) tool and Google E-E-A-T principles. Inter-rater reliability was excellent (ICC = 0.97 for EQIP, κ = 0.89 for E-E-A-T). A significant difference was found between chatbots in terms of readability scores (Gunning Fox Index p = 0.008, Flesch-Kincaid Grade Level p < 0.001), with all responses requiring education levels above the recommended 6th-8th grade. However, significant differences emerged in information quality (EQIP, p < 0.001; E-E-A-T, p < 0.001). Gemini demonstrated superior performance in both EQIP (60.2 ± 6.92) and E-E-A-T scores (13.5) compared to all other chatbots. AI chatbots show potential for patient education but produce content with readability levels too complex for general audiences. Significant quality variations exist between models. These findings emphasize the need for collaboration between healthcare professionals and AI developers to create more accessible, reliable health information systems.

OBJECTIVES:To evaluate the role of neoadjuvant chemotherapy in the final treatment plan and its impact on survival in bladder cancer patients who were diagnosed with variant histology in the radical cystectomy specimen and whose diagnostic accuracy was achieved with the previous transurethral resection of the bladder specimen. METHODS:In this retrospective multicenter study, data from 221 patients across 9 centers were analyzed between January 2012 and January 2022. The primary endpoint was overall, cancer-specific, recurrence-free, and metastasis-free survival rates among patients with and without neoadjuvant chemotherapy, and the secondary endpoint was to identify independent predictors of survival. The Kaplan-Meier method was used to estimate overall survival, cancer-specific survival, recurrence-free survival, and metastasis-free survival, and multivariate analyses were performed using the Cox-regression model. RESULTS:Kaplan-Meier estimates of overall, cancer-specific, recurrence-free, and metastasis-free survival demonstrated no significant difference between two groups. Cox multifactorial analysis revealed that the age (HR 1.030, 95% CI 1.003-1.057, p = 0.027), presence of pT4 tumor stage (HR 3.861, 95% CI 1.303-11.494, p = 0.015), and pN+ (HR 2.288, 95% CI 1.475-3.550, p < 0.001) at radical cystectomy histopathology were independent predictors of overall survival; presence of pT4 tumor stage and pN+ at radical cystectomy histopathology were independent predictors of cancer-specific survival (HR 8.245, 95% CI 1.873-36.292, p = 0.005 and HR 1.792, 95% CI 1.049-3.061, p = 0.033) and metastasis-free survival (HR 9.957, 95% CI 1.286-77.073, p = 0.028 and HR 2.949, 95% CI 1.674-5.197, p < 0.001); and the age (HR 1.047, 95% CI 1.006-1.090, p = 0.025) and pN+ at radical cystectomy histopathology (HR 4.150, 95% CI 1.917-8.981, p < 0.001) were independent predictors of recurrence-free survival. CONCLUSION:Neoadjuvant chemotherapy does not provide any survival advantage in variant histology; therefore, considering the disadvantages, such as delaying radical cystectomy, which can lead to inadvertent disease progression and chemotherapy-related toxicities, cautious should be exercised when administering neoadjuvant chemotherapy.

Background:Erectile dysfunction (ED) is a significant complication following penile fracture repair, and early prediction is critical for clinical management. Aim:To evaluate the effectiveness of machine learning (ML) algorithms in predicting the development of severe ED after penile fracture repair and to identify complex risk factors beyond the scope of traditional statistical methods. Methods:A retrospective analysis was conducted using data from 547 patients who underwent surgical repair for penile fracture between January 2020 and June 2024 at 23 urology centers affiliated with the Reconstructive Urology and Trauma Study Group of the Urological Surgery Society. Patients were categorized into two groups based on their International Index of Erectile Function-5 scores at six months postoperatively: severe ED (+) (≤7) and ED (-) (>7). Eleven different ML classifiers were evaluated to determine the most predictive models. Four distinct resampling techniques were employed to address class imbalance in the dataset. Feature importance analysis was also performed to identify the most influential variables contributing to ED risk. Outcomes:This study was conducted to enable the early identification of patients at high risk of developing severe ED following penile fracture surgery. Results:Logistic Regression, Gaussian Naive Bayes, and Linear Support Vector Machine emerged as the best-performing algorithms on the original dataset, with Area Under the Curve (AUC) scores of 0.81, 0.78, and 0.76, respectively. On the Synthetic Minority Over-sampling Technique (SMOTE)-resampled dataset, Quadratic Discriminant Analysis (QDA) achieved an AUC of 0.85, while the Artificial Neural Network (ANN) reached an AUC of 0.84. On the SMOTE-resampled dataset, QDA achieved a ROC-AUC of 0.85 (95% CI: 0.75-0.93), whereas on the SMOTE-Tomek Link-resampled dataset, the ANN attained a ROC-AUC of 0.84 (95% CI: 0.71-0.94). The most critical predictors of severe ED were age, comorbidities, tunical tear length, and time to surgery. Urethral injuries were not significant contributors, as all were minor and managed conservatively without urethroplasty. Clinical Implications:Integration of ML-based prediction models into clinical workflows could support early risk stratification and individualized patient care, ultimately improving postoperative functional outcomes. Strengths and Limitations:This study benefits from a large, multicenter dataset and a comparative analysis of multiple ML algorithms. However, its retrospective nature and inter-center variability in data reporting may limit generalizability. Conclusion:ML algorithms are effective and reliable tools for predicting severe ED after penile fracture repair and may enhance personalized postoperative management. Eliminating class imbalance in the data with resampling techniques improves model performance.

Introduction: Many different treatment options exist for pediatric stone disease (PSD). We conducted a survey among urologists in Turkey to find out which diagnostic and therapeutic method urologists choose for stones of different localization and size in pediatric patients of varying age groups. Materials and Methods: A survey on treatment options in various PSD was developed for urologists working in hospitals of different statuses. The survey consisted of 36 multiple-choice questions, and the average response time was 5 minutes. The measure taken to avoid repetitive responses was that the survey could only be completed once from an internet protocol. Results: The number of respondents was 95. 91.67%, 89.47%, and 80.21% of the participants preferred ultrasonography as the diagnostic method in the 0-2, 2-6, and 6-18 age ranges, respectively. In treating staghorn kidney stones between 0-2 and 2-6 years, mini percutaneous nephrolithotomy (PCNL) was preferred most frequently, followed by standard PCNL. In all age groups, shockwave lithotripsy was the most common procedure for symptomatic pelvic stones smaller than 10 mm, followed by retrograde intrarenal surgery in the second frequency. Endoscopic surgery was the most preferred method for bladder stones smaller than 2 cm in all age groups. Conclusion: The management of urinary tract stones in pediatric patients involves a complex set of processes. The sole aim is not to achieve stone-free management. Urologists in Turkey act following the guidelines. However, this is not always possible due to lack of facilities. The necessary facilities for urologists need to be improved.

To systematically assess the effectiveness and safety of retrograde intrarenal surgery (RIRS) versus percutaneous nephrolithotomy (PCNL) in treating lower pole stones. PubMed, Ovid MEDLINE, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), and EMBASE were researched to identify relevant studies up to May 2018. Based on keyword searches, we explored 1972 studies; following screening and eligibility evaluation, 414 studies were removed for various reasons, including 11 possibly relevant studies for this systematic review. A total of 1342 patient data were interpreted (PCNLn = 688; RIRS n = 654). The stone-free rate (SFR) in ten studies following the PCNL operation varies from 68 to 98.3

INTRODUCTION:This study evaluates the impact of chronic kidney disease (CKD) stages on stone-free rates (SFR) and renal function outcomes after percutaneous nephrolithotomy (PCNL). Additionally, it examines the predictive role of the CROES and Guy's Stone Score (GSS) systems. METHODS:Data from 2994 patients who underwent PCNL between 2007 and 2024 were retrospectively analyzed. Patients were classified into four CKD groups based on preoperative estimated glomerular filtration rate (eGFR). SFR, complication rates, and postoperative renal function changes were assessed. RESULTS:SFR was significantly lower in advanced CKD stages (p < 0.001), with the lowest in Group A (GFR < 30, 64.1%) and highest in Group D (GFR > 90, 79.1%). Postoperative eGFR increased in CKD stage 4-5 but declined in normal kidney function groups. Complication rates were higher in advanced CKD stages (p = 0.031). CROES and GSS scores correlated with stone complexity and surgical outcomes (p < 0.001). CONCLUSION:Advanced CKD is associated with lower SFR, greater surgical complexity, and higher complication rates. PCNL remains an effective treatment, particularly in CKD patients, with potential postoperative renal function improvement. Utilizing predictive scoring systems can optimize patient selection and surgical planning. Further prospective studies are needed to validate these findings.

Objective: This bibliometric analysis examines the evolution of prostate cancer (PCa) research and evaluates the impact of machine learning and artificial intelligence (AI) on its diagnosis, classification, and treatment. Materials and Methods: Articles published between 1997 and 2025 were analysed using the Web of Science Core Collection database. VOSviewer and Bibliometrix software was utilized for bibliometric analysis. Terms such as "PCa", "machine learning (ML)", "deep learning" and "AI" were included in the search strategy. The number of publications, the most cited studies, author collaborations and country collaborations, thematic trends, and citation networks were visualised. Results: A total of 3,277 articles were analysed. The in augural article was published in 1997. Over the past five years, there has been a significant increase in the number of articles published. The United States and China are the countries with the highest number of publications, and the most influential authors and institutions are concentrated in these countries. A marked upward trend has been observed in ML applications for PCa diagnosis, risk stratification, and treatment planning. Conclusion: The use of AI and ML in PCa research has grown significantly over the last 20 years. However, most of the existing models have been tested with retrospective data, and more multicenter and prospective studies are needed for clinical applications. Comprehensive clinical validation is essential before AI-based systems can be reliably implemented.

This study aimed to identify the risk factors associated with prolonged urine leakage (PUL) following pediatric percutaneous nephrolithotomy (PCNL) with a specific focus on the impact of lithotripter type. Data from 847 pediatric PCNL patients treated between August 1997 and February 2024 were collected. Patients were categorized into two groups based on the urine leakage time: prolonged leakage (> 24 h) and normal leakage. Logistic regression analysis was used to identify determinants of prolonged urine leakage. The study found that the use of laser lithotripters (LL) significantly increased the risk of prolonged urine leakage compared with pneumatic lithotripters (PL) (OR, 3.1; 95

PCNL, a minimally invasive surgical technique for kidney stone removal, relies on achieving stone-free status, which various scoring systems aim to predict. This study assesses the predictive accuracy of the Clinical Research Office of the Endourological Society (CROES) and Guy’s Stone Score (GSS) systems in determining stone-free rates following percutaneous nephrolithotomy (PCNL) in pediatric patients. A retrospective analysis was conducted on 580 pediatric patients who underwent PCNL at Çukurova University Urology Clinic between January 2007 and March 2024. Patients were categorized into two groups based on postoperative stone status: Group 1 and Group 2. CROES and GSS scores were calculated for each patient. The association between these scores and stone-free status, as well as postoperative complications, was statistically analyzed. Additionally, subgroup analyses were performed based on age groups. The study showed that 83.7% of patients achieved a stone-free condition postoperatively. Significant differences were found between the stone-free and residual stone groups regarding stone burden and operative time (p < 0.001). CROES had high accuracy for predicting stone-free outcomes (p < 0.001), while GSS was also effective in predicting both stone-free rates and complications. CROES was less effective in predicting complications. Both CROES and GSS are valuable for predicting PCNL outcomes in pediatric patients. While CROES is more reliable for stone-free rates, GSS better predicts complications. However, their limitations highlight the need for pediatric-specific scoring models. Until such models are developed, these systems should be used with caution alongside individualized clinical assessments.

OBJECTIVE:Molecular docking studies were conducted to assess the binding affinities of five potential inhibitor candidates [PDB (Protein Data Bank) ID: 6L6E] against Phosphodiesterase 5 (PDE5), with Sildenafil used as the reference compound. The aim of this study is to reveal the potential inhibitory role of plant-derived compounds compared to Sildenafil, a PDE5 inhibitor. MATERIALS AND METHODS:Autodock Vina v. 1.2.5 software was used to dock the protein and each ligand individually. Molecular dynamics simulations assessed the binding affinity of two compounds to the Phosphodiesterase 5A1 (PDE5 A1) enzyme and were carried out using GROMACS 2022.2 RESULTS: Boesenbergin A exhibited the highest affinity at -8.8 kcal/mol, followed by Ginkolide B at -8.5 kcal/mol, Sildenafil at -8.1 kcal/mol, Montanol at -7.8 kcal/mol, Beta-sitosterol at -7.1 kcal/mol, and Eugenol acetate at -6.9 kcal/mol, ranked in descending order. As a result of molecular docking studies, molecular dynamic simulations were performed for Boesenbergin A, which has the highest affinity, and Sildenafil, which is the standard molecule. CONCLUSIONS:Among the two ligands tested, Boesenbergin A exhibited superior binding affinity, surpassing even the standard molecule, Sildenafil. This suggests their potential for modulating enzyme activity and potential relevance in erectile dysfunction treatment.

Objective: In this study, we investigated the prognostic values of various pathological and inflammatory parameters in patients with high-grade lamina propriainvasive (T1G3) bladder cancer (BC). Materials and Methods: Between 2006 and 2018, patients with pathological evaluation of T1G3 bladder urothelial carcinoma in our institution who did not meet the exclusion criteria were included in the study. Parameters such as gender, tumor diameter, tumor number, lamina propria invasion depth, presence of carcinoma in situ, presence of lymphovascular invasion (LVI), presence of variant histology, lymphocyte monocyte ratio (LMR), platelet lymphocyte ratio (PLR), neutrophil lymphocyte ratio (NLR), and systemic inflammatory markers (SIM) were statistically analyzed. Results: After the exclusion criteria were evaluated, 76 patients were included in the study from 157 patients. Recurrence was observed in 37 (48.68%) patients, and progression was observed in 21 (27.63%) patients. A significant relationship was discovered between LMR (p<0,001), PLR (p<0.004), NLR (p<0.002), tumor diameter (p<0.002), number of tumors (p<0,007), and SIM score (p<0,001) with the probability of recurrence. The probability of progression was associated with NLR (p<0.023), LVI (p<0.005), tumor diameter (p<0.012) and tumor number (p<0.001). A significant relationship was found between SIM (p<0.041) and recurrencefree survival. We found a significant relationship between LVI (p<0.022) and progression -free survival. Conclusions: In this study, we found positive correlations between some inflammatory markers and recurrence/progression in patients with T1G3 BC. According to our study, inflammatory parameters such as NLR, PLR, LMR, and SIM score should be evaluated while investigating the possibility of recurrence/progression in patients with T1G3 BC.