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Zhang D, Zhang Y, Yang S. Non-linear relationship between preoperative albumin-globulin ratio and postoperative pneumonia in patients with hip fracture. Int J Orthop Trauma Nurs 2024; 54:101098. [PMID: 38608342 DOI: 10.1016/j.ijotn.2024.101098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 03/23/2024] [Accepted: 03/26/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND AND OBJECTIVE Postoperative pneumonia (POP) is the leading cause of death among patients with hip fractures. Simple and cost-effective markers can be used to assess the risk of these patients. This study aims to investigate the association between POP and preoperative albumin-globulin ratio (AGR) in patients with hip fractures. METHODS A retrospective analysis was conducted on data from 1417 hip fracture patients admitted to the Department of Orthopaedics at the hospital. Generalized additive and logistic regression models were used to determine both linear and non-linear associations between preoperative AGR and POP. A two-piece regression model was employed to determine the threshold effect. RESULTS The study included 1417 participants, with a mean age of 77.57 (8.53) years and 26.96% (382/1417) male patients. The prevalence of POP was 6.21%. Following full covariate adjustment, each unit increase in AGR was associated with a 79% reduction in the incidence of POP (OR, 0.23; 95% CI: 0.08-0.63; P = 0.0046). The inflection point was found to be 1.33 using a two-piecewise regression model. For each unit increase in AGR on the left side of the inflection point, the incidence of POP decreased by 93% (OR, 0.07; 95%CI: 0.02-0.34; P = 0.0010). However, there was no statistically significant correlation on the right side of the inflection point (OR, 0.84; 95% CI: 0.17-4.10; P = 0.8287). CONCLUSION There exists a non-linear association between preoperative AGR and the incidence of POP in elderly hip fracture patients. When AGR is less than 1.33, the incidence of POP is negatively correlated with AGR. However, there is no correlation when AGR is greater than 1.33.
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Affiliation(s)
- Daxue Zhang
- School of Nursing, Anhui Medical University, Hefei, China; Teaching Office, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China
| | - Yu Zhang
- Department of Orthopedics, Zhejiang Hospital, Hangzhou, China
| | - Shiwei Yang
- School of Nursing, Anhui Medical University, Hefei, China; Teaching Office, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China.
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Li Y, Xu H, Lin T, Zhang J, Ai J, Zhang S, Le W, Tan P, Zhang P, Wei Q, Zheng X, Yang L. Preoperative low plasma creatine kinase levels predict worse survival outcomes in bladder cancer after radical cystectomy. Int Urol Nephrol 2024; 56:2215-2225. [PMID: 38315281 DOI: 10.1007/s11255-024-03957-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/13/2024] [Indexed: 02/07/2024]
Abstract
BACKGROUND AND AIMS To evaluate the prognostic significance of preoperative creatine kinase (CK) levels in bladder cancer (BCa) patients who underwent radical cystectomy (RC). MATERIALS AND METHODS 570 BCa patients with RC were identified between 2010 and 2020. 108.5 U/L of CK levels were defined as the cutoff value. Logistic regression analysis and Cox regression models were performed to evaluate the association between CK levels and oncologic outcomes. Subgroup analyses were performed to address cofounding factors. RESULTS Preoperative low CK levels were associated with worse recurrence-free survival (RFS, log-rank P = 0.001) and overall survival (OS, log-rank P = 0.002). Multivariate analysis revealed that preoperative low CK levels were an independent predictor for worse RFS (hazard ratio [HR]: 1.683; P < 0.001) and OS (HR: 1.567; P = 0.002). CONCLUSIONS The preoperative low CK level independently predicts worse survival outcomes in BCa after RC. Incorporating it into prediction models might be valuable to assist risk stratification.
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Affiliation(s)
- Yifan Li
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Hang Xu
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Tianhai Lin
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Jiapeng Zhang
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianzhong Ai
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Shiyu Zhang
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Weizhen Le
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Ping Tan
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Peng Zhang
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Qiang Wei
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xiaonan Zheng
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China.
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Lu Yang
- Department of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China.
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, 610041, China.
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Ji J, Zhang T, Zhu L, Yao Y, Mei J, Sun L, Zhang G. Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma. BMC Cancer 2024; 24:725. [PMID: 38872141 PMCID: PMC11170799 DOI: 10.1186/s12885-024-12467-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 06/03/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated with radical cystectomy (RC). METHODS We retrospectively collected demographic, pathological, imaging, and laboratory information of BUC patients who underwent RC and bilateral lymphadenectomy in our institution. Patients were randomly categorized into training set and testing set. Five ML algorithms were utilized to establish prediction models. The performance of each model was assessed by the area under the receiver operating characteristic curve (AUC) and accuracy. Finally, we calculated the corresponding variable coefficients based on the optimal model to reveal the contribution of each variable to LNM. RESULTS A total of 524 and 131 BUC patients were finally enrolled into training set and testing set, respectively. We identified that the support vector machine (SVM) model had the best prediction ability with an AUC of 0.934 (95% confidence interval [CI]: 0.903-0.964) and accuracy of 0.916 in the training set, and an AUC of 0.855 (95%CI: 0.777-0.933) and accuracy of 0.809 in the testing set. The SVM model contained 14 predictors, and positive lymph node in imaging contributed the most to the prediction of LNM in BUC patients. CONCLUSIONS We developed and validated the ML models to preoperatively predict LNM in BUC patients treated with RC, and identified that the SVM model with 14 variables had the best performance and high levels of clinical applicability.
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Affiliation(s)
- Junjie Ji
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tianwei Zhang
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ling Zhu
- Shandong Key Laboratory of Digital Medicine and Computer Assisted Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yu Yao
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jingchang Mei
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lijiang Sun
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Guiming Zhang
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China.
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Klemm J, Shariat SF, Laukhtina E, Rajwa P, Vetterlein MW, Schuettfort VM, von Deimling M, Dahlem R, Fisch M, Rink M. Impact of Preoperative Plasma Potassium Levels on Oncological Outcomes, Major Complications, and 30-Day Mortality in Bladder Cancer Patients Undergoing Radical Cystectomy. Clin Genitourin Cancer 2024:102079. [PMID: 38614853 DOI: 10.1016/j.clgc.2024.102079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 03/14/2024] [Accepted: 03/15/2024] [Indexed: 04/15/2024]
Abstract
INTRODUCTION AND OBJECTIVES We examined the impact of preoperative plasma potassium levels (PPLs) on outcomes in patients undergoing radical cystectomy (RC) for urothelial carcinoma of the bladder (UCB), hypothesizing that potassium imbalances might influence outcomes. PATIENTS AND METHODS In this retrospective study, 501 UCB patients undergoing RC from 2009 to 2017 at a tertiary center were analyzed. Blood samples collected a week prior to surgery defined normal and abnormal PPL based on institutional standards. We assessed overall survival (OS), cancer-specific survival (CSS), recurrence-free survival (RFS), postoperative complications, 30-day mortality, and non-organ confined disease. Kaplan-Meier estimates, Cox proportional hazards, logistic regression, and decision curve analyses (DCA) were employed. RESULTS 63 (13%) patients had abnormal preoperative PPLs, with 50 (10%) elevated and 13 (2.5%) decreased. In a 59 months median follow-up, 152 (31%) had disease recurrence, 197 (39%) died from any cause, and 119 (24%) from UCB. Multivariable cox regression analyses adjusting for perioperative parameters demonstrated abnormal PPL was associated with worse OS (HR=1.9, P=0.009), CSS (HR=2.8, P<0.001) and RFS (HR=2.1; P=0.007). Elevated preoperative PPLs also demonstrated significant associations with adverse outcomes in OS, CSS, and RFS (all P<0.05). In multivariable logistic regression analyses, abnormal and elevated PPLs were not associated with 30-day mortality, major 30-day postoperative complications, positive nodal disease, pT3/4 stage, and non-organ confined disease (all P>0.05). CONCLUSION Abnormal and elevated preoperative PPLs correlate with adverse oncologic outcomes in UCB patients treated with RC. Pending external validation, preoperative PPLs might be a cost-effective, easily obtainable supplemental biomarker for enriching accuracy of outcome prediction in this highly variable maladie.
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Affiliation(s)
- Jakob Klemm
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Research center for Evidence Medicine, Urology department Tabriz University of Medical Sciences, Tabriz, Iran; Department of Urology, University of Texas Southwestern, Dallas, TX; Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Malte W Vetterlein
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Victor M Schuettfort
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Markus von Deimling
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Roland Dahlem
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Margit Fisch
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael Rink
- Department of Urology, Katholisches Marienkrankenhaus, Hamburg, Germany
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Laurie MA, Zhou SR, Islam MT, Shkolyar E, Xing L, Liao JC. Bladder Cancer and Artificial Intelligence: Emerging Applications. Urol Clin North Am 2024; 51:63-75. [PMID: 37945103 PMCID: PMC10697017 DOI: 10.1016/j.ucl.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023]
Abstract
Bladder cancer is a common and heterogeneous disease that poses a significant burden to the patient and health care system. Major unmet needs include effective early detection strategy, imprecision of risk stratification, and treatment-associated morbidities. The existing clinical paradigm is imprecise, which results in missed tumors, suboptimal therapy, and disease progression. Artificial intelligence holds immense potential to address many unmet needs in bladder cancer, including early detection, risk stratification, treatment planning, quality assessment, and outcome prediction. Despite recent advances, extensive work remains to affirm the efficacy of artificial intelligence as a decision-making tool for bladder cancer management.
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Affiliation(s)
- Mark A Laurie
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA; Institute for Computational and Mathematical Engineering, Stanford University School of Engineering, Stanford, CA 94305, USA
| | - Steve R Zhou
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA
| | - Md Tauhidul Islam
- Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA
| | - Eugene Shkolyar
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive Room G204, Stanford, CA 94305-5847, USA
| | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA 94304, USA; Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA.
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Hu B, Yan M, Huang S, Liang H, Lian W. Association between platelet‑to‑lymphocyte ratio and serum prostate specific antigen. Mol Clin Oncol 2024; 20:10. [PMID: 38213661 PMCID: PMC10777469 DOI: 10.3892/mco.2023.2708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 11/20/2023] [Indexed: 01/13/2024] Open
Abstract
There is evidence that the systemic inflammatory response may have an impact on prostate-specific antigen (PSA) levels. However, the relationship between the platelet-to-lymphocyte ratio (PLR) and PSA remains unclear. As a result, the relationship between PLR and PSA using the National Health and Nutrition Examination Survey (NHANES) database was examined. After the screening, 6,638 participants out of 52,186 in the NHANES survey conducted between 2001 to 2010 were suitable for the present study. The PLR was the independent variable in the present study, and PSA was the dependent variable. The selected subjects in the present study had an average age of 58.563±11.848 years. After controlling for covariates, the results showed that with every increase in PLR, the PSA concentration increased by 0.004 ng/ml (0.001, 0.007). This difference was statistically significant. Furthermore, a smoothing curve based on a fully adjusted model was created to investigate the possibility of a linear relationship between PLR and PSA concentration in men from USA. In men from USA, an independent and positive correlation between PLR and PSA was identified, which could potentially result in overdiagnosis of asymptomatic prostate cancer in populations with higher PLR levels.
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Affiliation(s)
- Bowen Hu
- Department of Urology, The People's Hospital of Longhua, Shenzhen, Guangdong 518000, P.R. China
| | - Minbo Yan
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, P.R. China
| | - Shuchang Huang
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, P.R. China
| | - Hui Liang
- Department of Urology, The People's Hospital of Longhua, Shenzhen, Guangdong 518000, P.R. China
| | - Wenfei Lian
- Department of Urology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong 519000, P.R. China
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Malik S, Wu J, Bodnariuc N, Narayana K, Gupta N, Malik M, Kwong JC, Khondker A, Johnson AE, Kulkarni GS. Existing trends and applications of artificial intelligence in urothelial cancer A scoping review. Can Urol Assoc J 2023; 17:E395-E401. [PMID: 37549345 PMCID: PMC10657228 DOI: 10.5489/cuaj.8322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
INTRODUCTION The use of artificial intelligence (AI) in urology is gaining significant traction. While previous reviews of AI applications in urology exist, there have been few attempts to synthesize existing literature on urothelial cancer (UC). METHODS Comprehensive searches based on the concepts of "AI" and "urothelial cancer" were conducted in MEDLINE , EMBASE , Web of Science, and Scopus. Study selection and data abstraction were conducted by two independent reviewers. Two independent raters assessed study quality in a random sample of 25 studies with the prediction model risk of bias assessment tool (PROBAST) and the standardized reporting of machine learning applications in urology (STREAM-URO) framework. RESULTS From a database search of 4581 studies, 227 were included. By area of research, 33% focused on image analysis, 26% on genomics, 16% on radiomics, and 15% on clinicopathology. Thematic content analysis identified qualitative trends in AI models employed and variables for feature extraction. Only 19% of studies compared performance of AI models to non-AI methods. All selected studies demonstrated high risk of bias for analysis and overall concern with Cohen's kappa (k)=0.68. Selected studies met 66% of STREAM-URO items, with k=0.76. CONCLUSIONS The use of AI in UC is a topic of increasing importance; however, there is a need for improved standardized reporting, as evidenced by the high risk of bias and low methodologic quality identified in the included studies.
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Affiliation(s)
- Shamir Malik
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON , Canada
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON , Canada
| | - Jeremy Wu
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON , Canada
| | - Nicole Bodnariuc
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON , Canada
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON , Canada
| | | | - Naveen Gupta
- Georgetown University School of Medicine, Georgetown University, Washington, DC, United States
- Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States
| | - Mikail Malik
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON , Canada
| | - Jethro C.C. Kwong
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON , Canada
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON , Canada
| | - Adree Khondker
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON , Canada
| | - Alistair E.W. Johnson
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON , Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON , Canada
- Vector Institute, Toronto, ON , Canada
| | - Girish S. Kulkarni
- Temerty Centre for AI Research and Education in Medicine, University of Toronto, Toronto, ON , Canada
- Division of Urology, Department of Surgery, University of Toronto, Toronto, ON , Canada
- Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON , Canada
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Ji J, Yao Y, Sun L, Yang Q, Zhang G. Development and validation of a preoperative nomogram to predict lymph node metastasis in patients with bladder urothelial carcinoma. J Cancer Res Clin Oncol 2023; 149:10911-10923. [PMID: 37318590 PMCID: PMC10423104 DOI: 10.1007/s00432-023-04978-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 06/07/2023] [Indexed: 06/16/2023]
Abstract
PURPOSE Predicting lymph node metastasis (LNM) in patients with bladder urothelial carcinoma (BUC) before radical cystectomy aids clinical decision making. Here, we aimed to develop and validate a nomogram to preoperatively predict LNM in BUC patients. METHODS Patients with histologically confirmed BUC, who underwent radical cystectomy and bilateral lymphadenectomy, were retrospectively recruited from two institutions. Patients from one institution were enrolled in the primary cohort, while those from the other were enrolled in the external validation cohort. Patient demographic, pathological (using transurethral resection of the bladder tumor specimens), imaging, and laboratory data were recorded. Univariate and multivariate logistic regression analyses were performed to explore the independent preoperative risk factors and develop the nomogram. Internal and external validation was conducted to assess nomogram performance. RESULTS 522 and 215 BUC patients were enrolled in the primary and external validation cohorts, respectively. We identified tumor grade, infiltration, extravesical invasion, LNM on imaging, tumor size, and serum creatinine levels as independent preoperative risk factors, which were subsequently used to develop the nomogram. The nomogram showed a good predictive accuracy, with area under the receiver operator characteristic curve values of 0.817 and 0.825 for the primary and external validation cohorts, respectively. The corrected C-indexes, calibration curves (after 1000 bootstrap resampling), decision curve analysis results, and clinical impact curves demonstrated that the nomogram performed well in both cohorts and was highly clinically applicable. CONCLUSION We developed a nomogram to preoperatively predict LNM in BUC, which was highly accurate, reliable, and clinically applicable.
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Affiliation(s)
- Junjie Ji
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yu Yao
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lijiang Sun
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Qingya Yang
- Department of Urology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China.
| | - Guiming Zhang
- Department of Urology, The Affiliated Hospital of Qingdao University, Qingdao, China.
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9
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von Deimling M, Schuettfort VM, D'Andrea D, Pradere B, Grossmann NC, Kawada T, Yanagisawa T, Majdoub M, Laukhtina E, Rajwa P, Quhal F, Mostafaei H, Fajkovic H, Teoh JYC, Moschini M, Karakiewicz PI, Fisch M, Rink M, Shariat SF. Predictive and Prognostic Role of the Neutrophil-to-Lymphocyte Ratio in Muscle Invasive Bladder Cancer Treated With Neoadjuvant Chemotherapy and Radical Cystectomy. Clin Genitourin Cancer 2023; 21:430-441. [PMID: 36781346 DOI: 10.1016/j.clgc.2023.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 01/18/2023] [Accepted: 01/21/2023] [Indexed: 01/27/2023]
Abstract
INTRODUCTION There is a persistent lack of validated biomarkers that identify patients most likely to benefit from neoadjuvant chemotherapy (NAC) in urothelial carcinoma of the bladder (UCB). Therefore, the purpose of this study was to investigate the predictive and prognostic impact of the pretreatment neutrophil-to-lymphocyte ratio (NLR) in UCB patients treated with NAC and radical cystectomy (RC). PATIENTS AND METHODS We conducted a retrospective analysis of an international-multicenter database comprising 404 UCB patients staged cT2-4N0-3M0. The cohort was split into low and high NLR using an optimal cutoff value determined by maximizing Youden's index. Logistic and Cox regression analyses were performed with respect to several clinical endpoints. The discriminative ability of the models and the additive discriminative value of NLR was assessed by calculating the area under receiver operating characteristics curves, C-index, and decision curve analysis (DCA). RESULTS A total of 169 patients (41.8%) had a high NLR, which was associated with a decreased probability of complete response (CR, OR: 0.24 [95% CI, 0.13-0.42], P < .001) and/or partial response (PR, OR: 0.33 [95% CI, 0.21-0.49], P < .001). Adding the NLR to predictive reference models significantly improved their accuracy for the prediction of both CR and PR. A high NLR was associated with poor survival outcomes in the pretreatment setting, however, it didn't meaningfully change the C-index based on the model. CONCLUSION We confirmed that an elevated NLR is an independent and clinically significant predictor of response to NAC and adverse pathological features in UCB treated with NAC plus RC. The accuracy of this biomarker in the age of immunotherapy warrants further evaluation.
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Affiliation(s)
- Markus von Deimling
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Victor M Schuettfort
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - David D'Andrea
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, La Croix Du Sud Hospital, Quint-Fonsegrives, France
| | - Nico C Grossmann
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Luzerner Kantonsspital, Luzern, Switzerland
| | - Tatsushi Kawada
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Takafumi Yanagisawa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, The Jikei University School of Medicine, Tokyo, Japan
| | - Muhammad Majdoub
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Hillel Yaffe Medical Center, Hadera, Israel
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Fahad Quhal
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - Hadi Mostafaei
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Research Center for Evidence Based Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Harun Fajkovic
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria
| | - Jeremy Yuen-Chun Teoh
- S.H. Ho Urology Centre, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
| | - Marco Moschini
- Department of Urology, Urological Research Institute, San Raffaele Scientific Institute, Milan, Italy
| | - Pierre I Karakiewicz
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Canada
| | - Margit Fisch
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael Rink
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia; Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan; Department of Urology, University of Texas Southwestern, Dallas, TX; Department of Urology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, NY; Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Department of Urology, Second Faculty of Medicine, Charles University, Prag, Czech Republic.
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Liu YS, Thaliffdeen R, Han S, Park C. Use of machine learning to predict bladder cancer survival outcomes: a systematic literature review. Expert Rev Pharmacoecon Outcomes Res 2023; 23:761-771. [PMID: 37306511 DOI: 10.1080/14737167.2023.2224963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 06/09/2023] [Indexed: 06/13/2023]
Abstract
INTRODUCTION The objective of this systematic review is to summarize the use of machine learning (ML) in predicting overall survival (OS) in patients with bladder cancer. METHODS Search terms for bladder cancer, ML algorithms, and mortality were used to identify studies in PubMed and Web of Science as of February 2022. Notable inclusion/exclusion criteria contained the inclusion of studies that utilized patient-level datasets and exclusion of primary gene expression-related dataset studies. Study quality and bias were assessed using the International Journal of Medical Informatics (IJMEDI) checklist. RESULTS Of the 14 included studies, the most common algorithms were artificial neural networks (n = 8) and logistic regression (n = 4). Nine articles described missing data handling, with five articles removing patients with missing data entirely. With respect to feature selection, the most common sociodemographic variables were age (n = 9), gender (n = 9), and smoking status (n = 3), with clinical variables most commonly including tumor stage (n = 8), grade (n = 7), and lymph node involvement (n = 6). Most studies (n = 10) were of medium IJMEDI quality, with common areas of improvement being the descriptions of data preparation and deployment. CONCLUSIONS ML holds promise for optimizing bladder cancer care through accurate OS predictions, but challenges related to data processing, feature selection, and data source quality must be resolved to develop robust models. While this review is limited by its inability to compare models across studies, this systematic review will inform decision-making by various stakeholders to improve understanding of ML-based OS prediction in bladder cancer and foster interpretability of future models.
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Affiliation(s)
- Yi-Shao Liu
- College of Pharmacy, The University of Texas at Austin, 2409 University Ave, Austin, TX, USA
| | - Ryan Thaliffdeen
- College of Pharmacy, The University of Texas at Austin, 2409 University Ave, Austin, TX, USA
| | - Sola Han
- College of Pharmacy, The University of Texas at Austin, 2409 University Ave, Austin, TX, USA
| | - Chanhyun Park
- College of Pharmacy, The University of Texas at Austin, 2409 University Ave, Austin, TX, USA
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11
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von Deimling M, D'Andrea D, Pradere B, Laukhtina E, Yanagisawa T, Kawada T, Majdoub M, Rajwa P, Pallauf M, Singla N, Soria F, Margulis V, Chlosta P, Karakiewicz PI, Roupret M, Teoh JYC, Fisch M, Rink M, Moschini M, Lotan Y, Shariat SF. Clinical value of cholinesterase in patients treated with radical nephroureterectomy for upper urinary tract carcinoma. World J Urol 2023; 41:1861-1868. [PMID: 37294372 PMCID: PMC10352439 DOI: 10.1007/s00345-023-04449-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 05/17/2023] [Indexed: 06/10/2023] Open
Abstract
PURPOSE To evaluate the prognostic value and the clinical impact of preoperative serum cholinesterase (ChoE) levels on decision-making in patients treated with radical nephroureterectomy (RNU) for clinically non-metastatic upper tract urothelial cancer (UTUC). METHODS A retrospective review of an established multi-institutional UTUC database was performed. We evaluated preoperative ChoE as a continuous and dichotomized variable using a visual assessment of the functional form of the association of ChoE with cancer-specific survival (CSS). We used univariable and multivariable Cox regression models to establish its association with recurrence-free survival (RFS), CSS, and overall survival (OS). Discrimination was evaluated using Harrell's concordance index. Decision curve analysis (DCA) was used to assess the impact on clinical decision-making of preoperative ChoE. RESULTS A total of 748 patients were available for analysis. Within a median follow-up of 34 months (IQR 15-64), 191 patients experienced disease recurrence, and 257 died, with 165 dying of UTUC. The optimal ChoE cutoff identified was 5.8 U/l. ChoE as continuous variable was significantly associated with RFS (p < 0.001), OS (p < 0.001), and CSS (p < 0.001) on univariable and multivariable analyses. The concordance index improved by 8%, 4.4%, and 7% for RFS, OS, and CSS, respectively. On DCA, including ChoE did not improve the net benefit of standard prognostic models. CONCLUSION Despite its independent association with RFS, OS, and CSS, preoperative serum ChoE has no impact on clinical decision-making. In future studies, ChoE should be investigated as part of the tumor microenvironment and assessed as part of predictive and prognostic models, specifically in the setting of immune checkpoint-inhibitor therapy.
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Affiliation(s)
- Markus von Deimling
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - David D'Andrea
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, La Croix Du Sud Hospital, Quint-Fonsegrives, France
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Takafumi Yanagisawa
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, The Jikei University School of Medicine, Tokyo, Japan
| | - Tatsushi Kawada
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Muhammad Majdoub
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, Hillel Yaffe Medical Center, Hadera, Israel
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Maximilian Pallauf
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
- Departments of Urology and Oncology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Urology, University Hospital Salzburg, Paracelsus Medical University, Salzburg, Austria
| | - Nirmish Singla
- Departments of Urology and Oncology, The James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Francesco Soria
- Division of Urology, Department of Surgical Sciences, San Giovanni Battista Hospital, University of Studies of Torino, Turin, Italy
| | - Vitaly Margulis
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Piotr Chlosta
- Department of Urology, Jagiellonian University, Cracow, Poland
| | - Pierre I Karakiewicz
- Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Canada
| | - Morgan Roupret
- Sorbonne University, GRC 5 Predictive Onco-Uro, AP-HP, Urology, Pitie-Salpetriere Hospital, Paris, France
| | - Jeremy Yuen-Chun Teoh
- S.H. Ho Urology Centre, Department of Surgery, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
| | - Margit Fisch
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael Rink
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marco Moschini
- Department of Urology, Urological Research Institute, Vita-Salute University, San Raffaele Scientific Institute, Milan, Italy
| | - Yair Lotan
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Vienna General Hospital, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
- Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
- Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
- Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria.
- Department of Urology, Weill Cornell Medical College, New York, NY, USA.
- Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
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Blood-Based Biomarkers as Prognostic Factors of Recurrent Disease after Radical Cystectomy: A Systematic Review and Meta-Analysis. Int J Mol Sci 2023; 24:ijms24065846. [PMID: 36982918 PMCID: PMC10056816 DOI: 10.3390/ijms24065846] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/15/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023] Open
Abstract
Survival outcomes after radical cystectomy (RC) for bladder cancer (BCa) have not improved in recent decades; nevertheless, RC remains the standard treatment for patients with localized muscle-invasive BCa. Identification of the patients most likely to benefit from RC only versus a combination with systemic therapy versus systemic therapy first/only and bladder-sparing is needed. This systematic review and meta-analysis pools the data from published studies on blood-based biomarkers to help prognosticate disease recurrence after RC. A literature search on PubMed and Scopus was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Articles published before November 2022 were screened for eligibility. A meta-analysis was performed on studies investigating the association of the neutrophil-to-lymphocyte ratio (NLR), the only biomarker with sufficient data, with recurrence-free survival. The systematic review identified 33 studies, and 7 articles were included in the meta-analysis. Our results demonstrated a statistically significant correlation between elevated NLR and an increased risk of disease recurrence (HR 1.26; 95% CI 1.09, 1.45; p = 0.002) after RC. The systematic review identified various other inflammatory biomarkers, such as interleukin-6 or the albumin-to-globulin ratio, which have been reported to have a prognostic impact on recurrence after RC. Besides that, the nutritional status, factors of angiogenesis and circulating tumor cells, and DNA seem to be promising tools for the prognostication of recurrence after RC. Due to the high heterogeneity between the studies and the different cut-off values of biomarkers, prospective and validation trials with larger sample sizes and standardized cut-off values should be conducted to strengthen the approach in using biomarkers as a tool for risk stratification in clinical decision-making for patients with localized muscle-invasive BCa.
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13
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Sarrió-Sanz P, Martinez-Cayuelas L, Lumbreras B, Sánchez-Caballero L, Palazón-Bru A, Gil-Guillén VF, Gómez-Pérez L. Mortality prediction models after radical cystectomy for bladder tumour: A systematic review and critical appraisal. Eur J Clin Invest 2022; 52:e13822. [PMID: 35642331 DOI: 10.1111/eci.13822] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/18/2022] [Accepted: 05/25/2022] [Indexed: 11/29/2022]
Abstract
INTRODUCTION To identify risk-predictive models for bladder-specific cancer mortality in patients undergoing radical cystectomy and assess their clinical utility and risk of bias. METHODS Systematic review (CRD42021224626:PROSPERO) in Medline and EMBASE (from their creation until 31/10/2021) was screened to include articles focused on the development and internal validation of a predictive model of specific cancer mortality in patients undergoing radical cystectomy. CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) were applied. RESULTS Nineteen observational studies were included. The main predictors were sociodemographic variables, such as age (18 studies, 94.7%) and sex (17, 89.5% studies), tumour characteristics (TNM stage (18 studies, 94.7%), histological subtype/grade (15 studies, 78.9%), lymphovascular invasion (10 studies, 52.6%) and treatment with chemotherapy (13 studies, 68.4%). C-index values were presented in 14 studies. The overall risk of bias assessed using PROBAST led to 100% of studies being classified as high risk (the analysis domain was rated to be at high risk of bias in all the studies), and 52.6% showed low applicability. Only 5 studies (26.3%) included an external validation and 2 (10.5%) included a prospective study design. CONCLUSIONS Using clinical predictors to assess the risk of bladder-specific cancer mortality is a feasibility alternative. However, the studies showed a high risk of bias and their applicability is uncertain. Studies should improve the conducting and reporting, and subsequent external validation studies should be developed.
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Affiliation(s)
- Pau Sarrió-Sanz
- Urology Services, University Hospital of San Juan de Alicante, Alicante, Spain
| | | | - Blanca Lumbreras
- Department of Public Health, History of Science and Gynecology, Miguel Hernández University, and CIBER en Epidemiología y Salud Pública, Alicante, Spain
| | | | - Antonio Palazón-Bru
- Department of Clinical Medicine, Miguel Hernández University, Alicante, Spain
| | | | - Luis Gómez-Pérez
- Department of Clinical Medicine, Miguel Hernández University, Alicante, Spain
- Urology Services, University General Hospital of Elx, Alicante, Spain
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14
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Sari Motlagh R, Schuettfort VM, Mori K, Katayama S, Rajwa P, Aydh A, Grossmann NC, Laukhtina E, Pradere B, Mostafai H, Quhal F, Abufaraj M, Lee R, Karakiewicz PI, Lotan Y, Comprate E, Moschini M, Gontero P, Shariat SF. Prognostic impact of insulin‐like growth factor‐I and its binding proteins, insulin‐like growth factor‐I binding protein‐2 and ‐3, on adverse histopathological features and survival outcomes after radical cystectomy. Int J Urol 2022; 29:676-683. [PMID: 35368130 PMCID: PMC9543826 DOI: 10.1111/iju.14869] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 03/08/2022] [Indexed: 12/20/2022]
Abstract
Objectives Insulin‐like growth factor‐I and its binding proteins are involved in cancer development, progression, and metastasis. In urothelial carcinoma, the impact of this pathway is still poorly investigated. The present large cohort study aimed to evaluate the association of preoperative circulating levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 on outcomes after radical cystectomy. Methods A retrospective cohort study of the plasma specimens from 1036 consecutive urothelial carcinoma patients who were treated with radical cystectomy. The primary and secondary outcomes were adverse histopathological features and survival outcomes. Binominal logistic regression and multivariable Cox regression analyses were performed to assess the association of plasma levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 with outcomes. Results On multivariable analysis adjusting for the effects of preoperative variables, lower insulin‐like growth factor‐I binding protein‐2 levels were associated with an increased risk of lymph node metastasis and (any non‐organ confined disease) any non‐organ confined disease. Insulin‐like growth factor‐I binding protein‐3 levels were also inversely independently associated with lymph node metastasis. Receiver operating characteristic curve analysis showed that the addition of insulin‐like growth factor‐I binding proteins biomarkers to a reference model significantly improved the discriminating ability for the prediction of lymph node metastasis (+10.0%, P < 0.001). On multivariable Cox regression models, lower levels of both insulin‐like growth factor‐I binding protein‐2 and ‐3 plasma levels were associated with recurrence‐free survival, cancer‐specific survival, and overall survival. insulin‐like growth factor‐I binding protein‐2 and ‐3 levels and improved the discrimination of a standard reference model for the prediction of recurrence‐free survival, cancer‐specific survival, and overall survival (+4.9%, 4.9%, 2.3%, respectively). Conclusions Preoperative insulin‐like growth factor‐I binding protein‐2 and ‐3 are significantly associated with features of biologically and clinically aggressive urothelial carcinoma. These biomarkers improved prognostic urothelial carcinoma models.
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Affiliation(s)
- Reza Sari Motlagh
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Men's Health and Reproductive Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran
| | - Victor M Schuettfort
- Department of Urology University Medical Center Hamburg‐Eppendorf Hamburg Germany
| | - Keiichiro Mori
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology The Jikei University School of Medicine Tokyo Japan
| | - Satoshi Katayama
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences Okayama Japan
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology Medical University of Silesia Zabrze Poland
| | - Abdulmajeed Aydh
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology King Faisal Medical City Abha Saudi Arabia
| | - Nico C Grossmann
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology University Hospital Zurich Zurich Switzerland
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Institute for Urology and Reproductive Health Sechenov University Moscow Russia
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
| | - Hadi Mostafai
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Research Center for Evidence Based Medicine Tabriz University of Medical Sciences Tabriz Iran
| | - Fahad Quhal
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Department of Urology King Fahad Specialist Hospital Dammam Saudi Arabia
| | - Mohammad Abufaraj
- Department of Special Surgery Jordan University Hospital, The University of Jordan Amman Jordan
| | - Richard Lee
- Department of Urology Weill Cornell Medical College New York New York USA
| | - Pierre I Karakiewicz
- Cancer Prognostics and Health Outcomes Unit University of Montreal Health Center Montreal Quebec Canada
| | - Yair Lotan
- Department of Urology University of Texas Southwestern Medical Center Dallas Texas USA
| | - Eva Comprate
- Department of Pathology Medical University of Vienna Vienna Austria
| | - Marco Moschini
- Unit of Urology/Division of Oncology URI, IRCCS Ospedale San Raffaele Milan Italy
| | - Paolo Gontero
- Division of Urology, Molinette Hospital University of Torino School of Medicine Torino Italy
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center Medical University of Vienna Vienna Austria
- Institute for Urology and Reproductive Health Sechenov University Moscow Russia
- Department of Urology Weill Cornell Medical College New York New York USA
- Department of Urology University of Texas Southwestern Medical Center Dallas Texas USA
- Department of Urology, Second Faculty of Medicine Charles University Prague Czech Republic
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15
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Modified Glasgow Prognostic Score as a Predictor of Recurrence in Patients with High Grade Non-Muscle Invasive Bladder Cancer Undergoing Intravesical Bacillus Calmette–Guerin Immunotherapy. Diagnostics (Basel) 2022; 12:diagnostics12030586. [PMID: 35328139 PMCID: PMC8947693 DOI: 10.3390/diagnostics12030586] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 02/17/2022] [Accepted: 02/23/2022] [Indexed: 01/09/2023] Open
Abstract
Background: A systemic inflammatory marker, the modified Glasgow prognostic score (mGPS), could predict outcomes in non-muscle-invasive bladder cancer (NIMBC). We aimed to investigate the predictive power of mGPS in oncological outcomes in HG/G3 T1 NMIBC patients undergoing Bacillus Calmette–Guérin (BCG) therapy. Methods: We retrospectively reviewed patient’s medical data from multicenter institutions. A total of 1382 patients with HG/G3 T1 NMIBC have been administered adjuvant intravesical BCG therapy, every week for 3 weeks given at 3, 6, 12, 18, 24, 30 and 36 months. The analysis of mGPS for recurrence and progression was performed using multivariable and univariable Cox regression models. Results: During follow-up, 659 patients (47.68%) suffered recurrence, 441 (31.91%) suffered progression, 156 (11.28%) died of all causes, and 67 (4.84%) died of bladder cancer. At multivariable analysis, neutrophil to lymphocyte ratio [hazard ratio (HR): 7.471; p = 0.0001] and erythrocyte sedimentation rate (ESR) (HR: 0.706; p = 0.006 were significantly associated with recurrence. mGPS has no statistical significance for progression (p = 0.076). Kaplan–Meier survival analysis showed a significant difference in survival among patients from different mGPS subgroups. Five-year OS was 93% (CI 95% 92–94), in patients with mGPS 0, 82.2% (CI 95% 78.9–85.5) in patients with mGPS 1 and 78.1% (CI 95% 60.4–70) in mGPS 2 patients. Five-year CSS was 98% (CI 95% 97–99) in patients with mGPS 0, 90% (CI 95% 87–94) in patients with mGPS 1, and 100% in mGPS 2 patients. Limitations are applicable to a retrospective study. Conclusions: mGPS may have the potential to predict recurrence in HG/G3 T1 NMIBC patients, but more prospective, with large cohorts, studies are needed to study the influence of systemic inflammatory markers in prediction of outcomes in NMIBC for a definitive conclusion.
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Grossmann NC, Schuettfort VM, Pradere B, Rajwa P, Quhal F, Mostafaei H, Laukhtina E, Mori K, Motlagh RS, Aydh A, Katayama S, Moschini M, Fankhauser CD, Hermanns T, Abufaraj M, Mun DH, Zimmermann K, Fajkovic H, Haydter M, Shariat SF. Impact of preoperative systemic immune-inflammation Index on oncologic outcomes in bladder cancer patients treated with radical cystectomy. Urol Oncol 2021; 40:106.e11-106.e19. [PMID: 34810077 DOI: 10.1016/j.urolonc.2021.10.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/19/2021] [Accepted: 10/18/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE To investigate the predictive and prognostic value of the preoperative systemic immune-inflammation index (SII) in patients undergoing radical cystectomy (RC) for clinically non-metastatic urothelial cancer of the bladder (UCB). METHODS Overall, 4,335 patients were included, and the cohort was stratified in two groups according to SII using an optimal cut-off determined by the Youden index. Uni- and multivariable logistic and Cox regression analyses were performed, and the discriminatory ability by adding SII to a reference model based on available clinicopathologic variables was assessed by area under receiver operating characteristics curves (AUC) and concordance-indices. The additional clinical net-benefit was assessed using decision curve analysis (DCA). RESULTS High SII was observed in 1879 (43%) patients. On multivariable preoperative logistic regression, high SII was associated with lymph node involvement (LNI; P = 0.004), pT3/4 disease (P <0.001), and non-organ confined disease (NOCD; P <0.001) with improvement of AUCs for predicting LNI (P = 0.01) and pT3/4 disease (P = 0.01). On multivariable Cox regression including preoperative available clinicopathologic values, high SII was associated with recurrence-free survival (P = 0.028), cancer-specific survival (P = 0.005), and overall survival (P = 0.006), without improvement of concordance-indices. On DCAs, the inclusion of SII did not meaningfully improve the net-benefit for clinical decision-making in all models. CONCLUSION High preoperative SII is independently associated with pathologic features of aggressive disease and worse survival outcomes. However, it did not improve the discriminatory margin of a prediction model beyond established clinicopathologic features and failed to add clinical benefit for decision making. The implementation of SII as a part of a panel of biomarkers in future studies might improve decision-making.
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Affiliation(s)
- Nico C Grossmann
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, University Hospital Zurich, Zurich, Switzerland
| | - Victor M Schuettfort
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Fahad Quhal
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - Hadi Mostafaei
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Research Center for Evidence Based Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Keiichiro Mori
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology, The Jikei University School of Medicine, Tokyo, Japan
| | - Reza S Motlagh
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Teheran, Iran
| | - Abdulmajeed Aydh
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Satoshi Katayama
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Department of Urology Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Marco Moschini
- Department of Urology, Luzerner Kantonsspital, Lucerne, Switzerland
| | | | - Thomas Hermanns
- Department of Urology, University Hospital Zurich, Zurich, Switzerland
| | - Mohammad Abufaraj
- Department of Special Surgery, Division of Urology, Jordan University Hospital, The University of Jordan, Amman, Jordan
| | - Dong-Ho Mun
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Kristin Zimmermann
- Department of Urology, Federal Armed Service Hospital Koblenz, Koblenz, Germany
| | - Harun Fajkovic
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Karl Landsteiner Society, Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria
| | - Martin Haydter
- Department of Urology, Landesklinikum Wiener Neustadt, Vienna, Austria
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria; Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia; Department of Special Surgery, Division of Urology, Jordan University Hospital, The University of Jordan, Amman, Jordan; Karl Landsteiner Society, Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria; Department of Urology, Weill Cornell Medical College, New York, NY; Department of Urology, University of Texas Southwestern, Dallas, TX.
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Peng L, Du C, Meng C, Li J, You C, Li X, Zhao P, Cao D, Li Y. Controlling Nutritional Status Score Before Receiving Treatment as a Prognostic Indicator for Patients With Urothelial Cancer: An Exploration Evaluation Methods. Front Oncol 2021; 11:702908. [PMID: 34722249 PMCID: PMC8548688 DOI: 10.3389/fonc.2021.702908] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 09/13/2021] [Indexed: 02/05/2023] Open
Abstract
Introduction This meta-analysis aims to assess whether the Controlling nutritional status (CONUT) score before treatment can be an independent predictor of the prognosis of patients with urothelial cancer (UC). Methods The system searches Web of Science, PubMed, MEDLINE, China National Knowledge Infrastructure (CNKI), and Cochrane Library, and the search time is up to April 2021. Use STATA 16.0 and Engauge Digitizer 4.1 software for data processing and statistical analysis. Results A total of 8 studies were included in this meta-analysis. The meta-analysis results show that compared with the low CONUT group, the high CONUT group has worse over survival (OS) [HR=1.58, 95%CI (1.34, 1.86), P=0.001], cancer-specific survival (CSS) [HR=2.03, 95%CI (1.25-3.29), P=0.04] and recurrence-free survival (RFS) [HR=1.97, 95%CI (1.15, 3.40), P=0.014]; for progression-free survival (PFS), or disease-free survival (DFS), the difference between the two groups was not statistically significant [HR=2.30, 95%CI (0.72, 7.32), P=0.158]. According to different carcinoma types, cut-off value, and region, subgroup analysis of OS was performed, and similar results were obtained. Conclusions Based on current evidence, this meta-analysis proves that the CONUT score of UC patients before treatment is an independent prognostic predictor. It performs well on OS, CSS, and RFS, but the conclusions on DFS/PFS need to be treated with caution. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021251890, identifier CRD42021251890.
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Affiliation(s)
- Lei Peng
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
| | - Chunxiao Du
- Department of Clinical Pharmacy, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Chunyang Meng
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
| | - Jinze Li
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Chengyu You
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
| | - Xianhui Li
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
| | - Pan Zhao
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
| | - Dehong Cao
- Department of Urology, Institute of Urology, West China Hospital, Sichuan University, Chengdu, China.,State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu, China
| | - Yunxiang Li
- Department of Urology, Nanchong Central Hospital, The Second Clinical College, North Sichuan Medical College (University), Nanchong, China
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Xie Z, Cai J, Sun W, Hua S, Wang X, Li A, Jiang J. Development and Validation of Prognostic Model in Transitional Bladder Cancer Based on Inflammatory Response-Associated Genes. Front Oncol 2021; 11:740985. [PMID: 34692520 PMCID: PMC8529162 DOI: 10.3389/fonc.2021.740985] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 09/16/2021] [Indexed: 01/18/2023] Open
Abstract
Background Bladder cancer is a common malignant type in the world, and over 90% are transitional cell carcinoma. While the impact of inflammatory response on cancer progression has been reported, the role of inflammatory response-associated genes (IRAGs) in transitional bladder cancer still needs to be understood. Methods In this study, IRAGs were download from Molecular Signature Database (MSigDB). The transcriptional expression and matched clinicopathological data were separately obtained from public databases. The TCGA-BLCA cohort was used to identify the differentially expressed IRAGs, and prognostic IRAGs were filtrated by univariate survival analysis. The intersection between them was displayed by Venn diagram. Based on least absolute shrinkage and selection operator (LASSO) regression analysis method, the TCGA-BLCA cohort was used to construct a risk signature. Survival analysis was conducted to calculate the overall survival (OS) in TCGA and GSE13507 cohort between two groups. We then conducted univariate and multivariate survival analyses to identify independently significant indicators for prognosis. Relationships between the risk scores and age, grade, stage, immune cell infiltration, immune function, and drug sensitivity were demonstrated by correlation analysis. The expression level of prognostic genes in vivo and in vitro were determined by qRT-PCR assay. Results Comparing with normal tissues, there were 49 differentially expressed IRAGs in cancer tissues, and 12 of them were markedly related to the prognosis in TCGA cohort for transitional bladder cancer patients. Based on LASSO regression analysis, a risk model consists of 10 IRAGs was established. Comparing with high-risk groups, survival analysis showed that patients in low-risk groups were more likely to have a better survival time in TCGA and GSE13507 cohorts. Besides, the accuracy of the model in predicting prognosis is acceptable, which is demonstrated by receiver operating characteristic curve (ROC) analysis. Age, stage, and risk scores variables were identified as the independently significant indicators for survival in transitional bladder cancer. Correlation analysis represented that the risk score was identified to be significantly related to the above variables except gender variable. Moreover, the expression level of prognostic genes in vivo and in vitro was markedly upregulated for transitional bladder cancer. Conclusions A novel model based on the 10 IRAGs that can be used to predict survival time for transitional bladder cancer. In addition, this study may provide treatment strategies according to the drug sensitivity in the future.
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Affiliation(s)
- Zhiwen Xie
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinming Cai
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenlan Sun
- Department of Geriatrics, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China
| | - Shan Hua
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xingjie Wang
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Anguo Li
- Department of Urology, The Fifth Peoples Hospital of Zunyi, Guizhou, China
| | - Juntao Jiang
- Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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19
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Laukhtina E, Schuettfort VM, D Andrea D, Pradere B, Mori K, Quhal F, Sari Motlagh R, Mostafaei H, Katayama S, Grossmann NС, Rajwa P, Zeinler F, Abufaraj M, Moschini M, Zimmermann K, Karakiewicz PI, Fajkovic H, Scherr D, Compérat E, Nyirady P, Rink M, Enikeev D, Shariat SF. Preoperative plasma level of endoglin as a predictor for disease outcomes after radical cystectomy for nonmetastatic urothelial carcinoma of the bladder. Mol Carcinog 2021; 61:5-18. [PMID: 34587660 PMCID: PMC9293216 DOI: 10.1002/mc.23355] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 09/07/2021] [Accepted: 09/18/2021] [Indexed: 11/07/2022]
Abstract
Elevated preoperative plasma level of endoglin has been associated with worse oncologic outcomes in various malignancies. The present large-scale study aimed to determine the predictive and prognostic values of preoperative endoglin with regard to clinicopathologic and survival outcomes in patients treated with radical cystectomy (RC) for nonmetastatic urothelial carcinoma of the bladder (UCB). We prospectively collected preoperative blood samples from 1036 consecutive patients treated with RC for UCB. Logistic and Cox regression analyses were undertaken to assess the correlation of endoglin levels with pathologic and survival outcomes, respectively. The AUC and C-index were used to assess the discrimination. Patients with adverse pathologic features had significantly higher median preoperative endoglin plasma levels than their counterparts. Higher preoperative endoglin level was independently associated with an increased risk for lymph node metastasis, ≥pT3 disease, and nonorgan confined disease (NOCD; all p < 0.001). Plasma endoglin level was also independently associated with cancer-specific and overall survival in both pre- and postoperative models (all p < 0.05), as well as with recurrence-free survival (RFS) in the preoperative model (p < 0.001). The addition of endoglin to the preoperative standard model improved its discrimination for prediction of lymph node metastasis, ≥pT3 disease, NOCD, and RFS (differential increases in C-indices: 10%, 5%, 5.8%, and 4%, respectively). Preoperative plasma endoglin is associated with features of biologically and clinically aggressive UCB as well as survival outcomes. Therefore, it seems to hold the potential of identifying UCB patients who may benefit from intensified therapy in addition to RC such as extended lymphadenectomy or/and preoperative systemic therapy.
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Affiliation(s)
- Ekaterina Laukhtina
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Victor M Schuettfort
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - David D Andrea
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Benjamin Pradere
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Keiichiro Mori
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, The Jikei University School of Medicine, Tokyo, Japan
| | - Fahad Quhal
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, King Fahad Specialist Hospital, Dammam, Saudi Arabia
| | - Reza Sari Motlagh
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Men's Health and Reproductive Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hadi Mostafaei
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Research Center for Evidence Based Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Satoshi Katayama
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan
| | - Nico С Grossmann
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, University Hospital Zurich, Zurich, Switzerland
| | - Pawel Rajwa
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Department of Urology, Medical University of Silesia, Zabrze, Poland
| | - Flora Zeinler
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Mohammad Abufaraj
- Department of Special Surgery, Division of Urology, Jordan University Hospital, The University of Jordan, Amman, Jordan
| | - Marco Moschini
- Department of Urology, Luzerner Kantonsspital, Lucerne, Switzerland.,Department of Urology and Division of Experimental Oncology, Urological Research Institute, Vita-Salute San Raffaele
| | - Kristin Zimmermann
- Department of Urology, Federal Armed Services Hospital Koblenz, Koblenz, Germany
| | - Pierre I Karakiewicz
- Division of Urology, Cancer Prognostics and Health Outcomes Unit, University of Montreal Health Center, Montreal, Canada
| | - Harun Fajkovic
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria
| | - Douglas Scherr
- Department of Urology, Weill Cornell Medical College, New York Presbyterian Hospital, New York, New York, USA
| | - Eva Compérat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Peter Nyirady
- Department of Urology, Semmelweis University, Budapest, Hungary
| | - Michael Rink
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dmitry Enikeev
- Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - Shahrokh F Shariat
- Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.,Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.,Karl Landsteiner Institute of Urology and Andrology, Vienna, Austria.,Department of Urology, Weill Cornell Medical College, New York, New York, USA.,Department of Urology, University of Texas Southwestern, Dallas, Texas, USA.,Department of Urology, Second Faculty of Medicine, Charles University, Prague, Czech Republic.,Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan
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