Impact of diabetes mellitus on oncologic outcomes in patients receiving robot- assisted radical cystectomy for bladder cancer

Impact of diabetes mellitus on oncologic outcomes in patients receiving robot- assisted radical cystectomy for bladder cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of diabetes mellitus on oncologic outcomes in patients receiving robot- assisted radical cystectomy for bladder cancer Gabriele Tuderti, Giuseppe Chiacchio, Riccardo Mastroianni, Umberto Anceschi, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4638244/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 May, 2024 Read the published version in Journal of Urology → Version 1 posted You are reading this latest preprint version Abstract Purpose Aim of this study is to investigate the association between DM and oncological outcomes among patients with muscle-invasive (MI) or high-risk non-muscle invasive (NMI) bladder cancer (BC) who underwent robot-assisted radical cystectomy with intracorporeal urinary diversion (RARC) Methods An IRB approved multi-institutional BC database was queried, including patients underwent RARC between January 2013 and June 2023. Patients were divided into two groups according to DM status. Baseline, clinical, perioperative, pathologic data were compared. Chi-square and Student t tests were performed to compare categorical and continuous variables, respectively. Kaplan-Meier method and Cox regression analyses were performed to assess the association between DM and oncologic outcomes. Results Out of 547 consecutive patients, 97 (17.7%) had DM. The two cohorts showed similar preoperative features, except for ASA score (p=0.01) and Hypertension rates (p0.12). DM patients displayed significantly lower 5-yr disease-free survival (DFS) (44.6% vs 63.3%, p=0.007), 5-yr cancer-specific survival (CSS) (45.1% vs 70.1%, p=0.001) and 5-yr Overall survival (OS) (39.9% vs 63.8%, p=0.001). At Multivariable Cox-regression analyses DM status was identified as independent predictor of worse cancer-specific survival (CSS) (HR 2.1; p=0.001) and overall survival (OS) (HR 2.05; p<0.001). Conclusion Among BC patients who underwent RARC, DM patients showed worse oncologic outcomes than the non-DM patients, with DM status playing an independent negative predicting role in CSS and OS. Future prospective studies are awaited, stimulating basic and translational research to identify possible mechanisms of interaction between DM and BC. Bladder cancer Diabetes mellitus Oncologic outcomes Radical cystectomy Robotic Figures Figure 1 Introduction Diabetes mellitus (DM) represents a chronic metabolic disorder and constitutes a highly significant public health concern. Impacting millions of people globally, DM might be responsible of severe acute and chronic complications, such as hyperglycemia-induced damage to nerves and blood vessels, leading to conditions like neuropathy, nephropathy, and an increased risk of heart disease and stroke [ 1 ]. According to the International Diabetes Federation, the number of individuals living with DM has risen dramatically, from 180 millions in 1980 to an estimated 529 million in 2021 [ 1 , 2 ]; these data translate to a global age-standardized prevalence of 6.1% [ 2 ]. On the other hand, Urothelial carcinoma of the bladder is a highly aggressive malignancy associated with substantial morbidity and mortality burdens [ 3 ]. In European countries, the age-standardized incidence rate is 20 per 100,000 individuals for men and 4.6 for women; furthermore, approximately 25% of patients diagnosed with bladder cancer (BC) present with muscle-invasive (MI) disease, which carries a poorer prognosis. At ten years, the disease-free survival (DFS) and overall survival (OS) rates for MIBC are 35% and 58%, respectively. Notably, the 5-yr OS rate plummets to only 18% for node-positive patients who undergo radical cystectomy (RC) [ 3 ]. Compelling evidence suggests an association between DM and increased incidence and mortality from various cancers [ 4 ]. As a matter of fact, several studies have revealed a link between DM and a rise in cancer incidence [ 5 ], along with a poorer prognosis in a range of malignancies [ 6 , 7 ], such as colorectal, breast, endometrial, liver, pancreatic, and bladder cancers [ 7 , 8 ]. Focusing on BC, it has been fully assessed that DM represents an independent predictor of disease recurrence and progression-free survival in patients with MIBC who underwent open radical cystectomy (ORC) [ 9 ]. However, other studies have failed to establish a clear association between the two diseases [ 10 , 11 ]. In the last decade, the technological advancements in BC treatment have witnessed a remarkable evolution, transitioning from open surgery to minimally invasive and robotic-assisted surgical approaches [ 12 , 13 ]. Given the established prevalence of DM and its potential association with oncological outcomes in urothelial carcinoma, and considered the increasing adoption of robotic surgery in the treatment of MIBC, this multicenter retrospective study aims to investigate the impact of DM on cancer-related outcomes in patients with MI or high-risk non-muscle invasive (NMI) BC undergoing robot-assisted radical cystectomy (RARC). Material and methods An IRB approved multi-institutional BC database was queried, including patients underwent RARC for MI or high-risk NMI BC in three high-volume centers between January 2013 and June 2023. Patients were divided into two groups according to DM status at the time of surgery. No type 1 DM patients were enrolled. We excluded patients who had metastasis at the time of RARC. Inclusion criteria were MI or recurrent high-grade urothelial NMIBC refractory to intravesical immunotherapy. Severe cardiovascular, respiratory or cognitive diseases, ejection fraction < 36%, retinal vascular diseases, presence of ventriculo-peritoneal shunt and previous major bowel surgeries were contraindications for robotic surgery. After surgery, ERAS protocol was applied, consisting of immediate post-operative nasogastric tube removal, fluid intake since 1st post-operative day (POD), solid intake at first flatus; patient were stimulated to leave the bed early, encouraging to be seat at 1st POD and move for a soft walking at 2nd POD. All RARC procedures were performed by expert surgeons, which had already carried out several robotic procedures, in terms of prostate and renal surgery, and had also a large experience in open ORC. The surgical team is usually composed by the console surgeon, the bed-side assistant surgeon, a urology resident, and a bed-side nurse. The type of urinary diversion (neobladder, ileal conduit, ureterocutaneostomy or pouch) was decided according of the preoperative and intraoperative characteristics of the patients. Baseline demographic, clinical, perioperative, pathologic data were compared. Baseline and preoperative characteristics, including age, BMI, gender, hypertension, smoking status, American Society of Anesthesiologists (ASA) score, neoadjuvant chemotherapy (Neo-CHT), preoperative Haemoglobin (Hgb) and preoperative estimated glomerular filtration rate (eGFR) were systematically recorded. Renal function was evaluated using serum creatinine and eGFR, calculated using the Modification of Diet in Renal Disease (MDRD) formula [ 14 ]. Perioperative data consisted of type of urinary diversion, mean hospital stay, operative time, and perioperative complications rates, which were documented according to the Clavien–Dindo (CD) classification system [ 15 ]. Major complications were defined by CD ≥ 3. Pathologic outcomes evaluated were pT stage, pN stage, lymph-node count, concomitant Cis and positive surgical margins (PSM) status. Statistical Analysis Categorical variables were described using frequencies and proportions. Continuous variables were reported using mean and standard deviation (SD). Chi-square and Student t tests were performed to compare categorical and continuous variables, respectively. The Kaplan-Meier method was performed to compare survival outcomes between the two cohorts of patients. Univariable and multivariable Cox regression analysis were used to identify independent predictors of DFS, cancer-specific survival (CSS) and OS. The significance level was set at < 0.05. All tests were two-sided, and statistical significance was defined as p < 0.05. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS v.21, IBM Corp., Armonk, NY, USA) and with the R statistical package (v.2.14.2) Results Patients, n Non-DM (450) DM (97) p value Age, yr, mean (SD) 65.8 (± 10) 67.9 (± 11.6) 0.06 BMI, mean (SD) 26.1 (± 7.3) 26 (± 4.2) 0.88 Male gender, n (%) 354 (78.7) 79 (81.4) 0.58 Smoking, n (%) 337 (74.9) 74 (76.3) 0.45 Hypertension, n (%) 224 (49.8) 68 (70.1) <0.001 ASA score, n(%) 1 2 3 4 22 (4.9) 302 (67.1) 120 (26.7) 6 (1.3) 2 (2.1) 52 (53.6) 40 (41.2) 3 (3.1) 0.01 Neoadjuvant CHT, n (%) 119 (26.4) 16 (16.5) 0.04 Preoperative Hgb, g/dl, mean (SD) 12.9 (± 1.9) 12.9 (± 1.8) 0.81 Preoperative eGFR, ml/min, mean (SD) 66 (± 37.5) 58.5 (± 37.4) 0.09 Table 1. Baseline and preoperative characteristics Out of 547 consecutive patients included in the study, 97 (17.7%) had DM. DM patients displayed a significantly higher rate of hypertension (70.1 % vs 49.8%, p <0.001) and comorbidities (ASA score ³ 3: 44.3% vs 28 %, p=0.01) (Table 1). Perioperative and pathologic data were reported in Table 2. Urinary diversion types were equally distributed in the two cohorts, with intracorporeal orthotopic neobladder (ION) being the most adopted diversions in both groups (No-DM 55.6% vs DM 43.3%, p= 0.20). There were no significant differences between the two groups in terms of length of mean hospital stay (No-DM 8.7 days vs DM 8.8 days, p=0.99) and mean operative time (No-DM 273.5 mins vs DM 269.3 mins, p=0.69). The two groups showed comparable overall perioperative complications rates (No-DM 42.1% vs DM 39.6%, p=0.72), as well as severe (Clavien grade > 2) complications rates (No-DM 8.2% vs DM 8.2%, p=1). No differences were detected in terms pT stage, pN stage and PSM status (all p>0.12). The mean lymph-node count was 27.1 vs 24.4 in No-DM and DM group, respectively (p=0.08). Concomitant Cis was reported in 150 (33.4%) pts in the No-DM group and in 35 (36.2%) pts in the DM group (p 0.63). (Table2.). Patients, n Non-DM (450) DM (97) p value Type of urinary diversion, n (%) Neobladder Ileal conduit Ureterocutaneostomy Pouch 250 (55.6) 94 (20.9) 102 (22.6) 4 (0.9) 42 (43.3) 24 (24.7) 29 (29.9) 2 (2.1) 0.20 Hospital stay, days, mean (± SD) 8.7 (± 8) 8.8 (± 11.3) 0.99 Operative time, min, mean (± SD) 273.5 (± 95.2) 269.3 (± 97) 0.69 Overall Perioperative complications, n (%) 189 (42.1) 38 (39.6) 0.72 Clavien 1-2 perioperative complications, n (%) 174 (38.7) 35 (36.3) 0.82 Clavien 3 perioperative complications, n (%) 37 (8.2) 8 (8.2) 1 pT stage, n (%) 0, a is 1 2 3 4 114 (25.4) 46 (10.3) 37 (8.2) 76 (16.7) 117 (26.1) 60 (13.3) 21 (21.3) 5 (5.3) 4 (4.3) 26 (26.6) 28 (28.7) 13(13.8) 0.13 pN stage, n (%) 0 1 2 3 355 (78.8) 26 (6) 59 (13) 10 (2.2) 72 (74.4) 9 (8.9) 11 (11.1) 5 (5.6) 0.22 Lymph-node count, mean (± SD) 27.1 (± 12.9) 24.4 (± 10.5) 0.08 Concomitant Cis, n (%) 150 (33.4) 35 (36.2) 0.63 Positive surgical margins, n (%) 12 (2.7) 0 (0) 0.13 Follow-up, median (IQR) 31.3 (± 31.7) 20.8 (± 24.7) 0.005 Table 2 . Perioperative and pathologic outcomes With reference to survival analysis, DM patients displayed a statistically significantly lower DFS (5-yr: 44.6% vs 63.3%, p=0.007), CSS (5-yr: 45.1% vs 70.1%, p=0.001) and OS (5-yr: 39.9% vs 63.8%, p=0.001) (Fig 1a-1b-1c). At Multivariable Cox-regression analyses, after adjustment for other covariates acknowledged for impacting on survival outcomes, DM status was identified as an independent predictor of lower CSS (HR 2.1, 95% CI 1.35-3.24; p=0.001; Table 3a) and lower OS (HR 2.05, 95% CI 1.43-2.96; p<0.001; Table 3b) but not of lower DFS (HR 1.43, 95% CI 0.94-2.18; p 0.08; Table 3c). Figure 1(1a,1b,1c): Kaplan-Meier analysis assessing DFS, CSS and OS probability over time between DM and Non-DM patients Table 3 (3a, 3b,3c) Univariable and multivariable cox regression analyses to identify independent predictors of CSS, OS and DFS Discussion Several studies have established an association between DM and an increased cancer incidence and poorer prognosis across various malignancies, including colorectal, breast, endometrial, liver, pancreatic, and BC [ 4 – 8 ]. The precise nature of this association remains under investigation. While some propose a direct causal relationship mediated by hyperinsulinemia and poor glycemic control [ 16 ], others suggest an indirect association driven by shared risk factors, among which one of the principal ones is obesity [ 17 ]. The crucial role that DM might play in worsening survival outcomes was initially debated about twenty years ago, when Coughlin et al. performed a prospective study, evaluating one million of American patients for a long-time period of 16 years, and identified DM as an independent risk factor for cancer specific mortality (CSM) in men (RR 1.43, 95% CI 1.14–1.80) [ 18 ]. Similar findings were reported by Campbell et al., in a study with a median follow up of 26 years, showing that the risk of death in DM male patients with BC was superior (RR 1.22, 95% CI 1.01–1.47) [ 19 ]. In addition, such association between DM and BC was highlighted in another multi-center study, in which the authors observed a positive correlation between DM and BC mortality, with higher fasting blood glucose levels associated with a greater risk of death [ 20 ]. Moreover, Zhu et al, in a cumulative meta-analysis, displayed a negative impact on BC mortality in DM men patients (RR 1.55, 95% CI 1.30–1.82) but also in DM female ones (RR 1.50, 95% CI 1.05–2.14) [ 21 ]. In the last decade, evidence supporting a negative impact of DM on oncologic outcomes in patients undergoing extirpative surgery for BC have been accumulating, with several data deriving from large cohorts studies. Accordingly, in a more recent meta-analysis, Xu et al. included and analyzed 21 cohorts studies, involving 13 millions participants, and reported that DM was associated with a higher risk of BC and cancer mortality (HR: 1.23; 95% CI 1.12–1.35) [ 8 ] . These results are in agreement with a systematic review conducted by Cantiello et al., where the effects of various comorbidities, such as smoking status, hypertension, obesity, and DM, on oncologic outcomes of BC were analyzed and well-established [ 5 ]. All the literature examining the relationship between DM and BC often refer to series in which patients were treated through an open approach, thus before the wide-spread diffusion and consequent adoption of robotic surgery for BC. As a matter of fact, although the open approach was the most widely adopted worldwide for several years, RARC has gained increasing popularity over the past decade. This is due to the potential benefits of a minimally invasive approach, such as lower morbidity, shorter hospital stays (LOS), and quicker patient recovery. The oncological effectiveness of RARC has been extensively studied, and its equivalence to ORC has been confirmed in recent randomized controlled trials (RCTs) [ 22 – 26 ]. In addition, long-term survival data of RARC have been adequately addressed in high-volume multicenter series, providing survival rates aligned with the largest open series [ 27 ]. Accordingly, a recent single center retrospective study including RARC-ICUD patients, reported long-term oncologic data, reinforcing the oncologic effectiveness of robotic approach (5-yr DFS 66.5%, 5-ys CSS 65.4%, 5-yr OS 61.5%) [ 28 ]. Having established the equivalence in terms of oncologic outcomes between the surgical approaches, our study investigated the impact of diabetes mellitus (DM) on oncological outcomes in patients with muscle-invasive or high-risk non-muscle invasive bladder cancer (BC) undergoing RARC. By analyzing our results, patients with DM had demonstrated to have worse oncologic outcomes, showing a 5-yr DFS significantly lower than patients without DM (44.6% vs 63.3%, log-rank p = 0.007). DM cohort displayed also significantly lower 5-yr CSS (45.1% vs 70.1%, log-rank p = 0.001) and 5-yr OS (39.9% vs 63.8%, log-rank p = 0.001). In corroboration of these findings, at Cox- regression MV analysis, DM has been shown to be a significant predictor of CSS, providing a 2.1-fold increased risk of cancer-related mortality (HR = 2.1, 95% CI 1.35–3.24, p = 0.001), and OS, providing a 2.05-fold increased risk of all-cause mortality (HR = 2.05, 95% CI 1.43–2.96, p < 0.001). The present paper is not devoid of limitations. Firstly, its retrospective design and a relatively small cohort, particularly regarding patients with DM, restrict our ability to analyze potentially significant factors like lymphovascular invasion, mixed histologic variants, and medication use (aspirin, statins). Secondly, the unassessed duration of DM introduces potential recall bias and the possibility of undetected cases. Thirdly, we did not analyze the potential differences in outcomes between DM patients receiving metformin and those not receiving it. Finally, the high-volume caseload of the centers and the need for advanced robotic surgical expertise [ 29 ] might affect the reproducibility of these outcomes in daily practice. Despite these limitations, our study contributes valuable insights to the limited existing literature exploring the association between DM and oncological outcomes in BC patients undergoing RARC. These findings may guide future research and clinical practice for managing urothelial carcinoma patients with DM in the era of robotic surgery. Conclusions Our study indicates that among BC patients who underwent RARC, those with DM experienced significantly worse oncological outcomes. DM status appears to be an independent negative predictor for both CSS and OS, providing a 2-fold increased risk of cancer-related and all-cause mortality. These findings warrant further validation through prospective studies. Additionally, focused investigations, both basic and translational, are awaited in order to uncover the biological mechanisms driving the interaction between DM and worsened BC outcomes. Declarations Authors’ Contribution G Tuderti: project development, Manuscript editing Data analysis G Chiacchio: Manuscript writing, Data analysis RMastroianni: Data analysis U Anceschi: Manuscript editing AM Bove: Data analysis, Manuscript editing A Brassetti: Data analysis, Manuscript editing S D'Annunzio: Data collection, Data analysis M Ferriero: Manuscript writing/editing, Data analysis L Misuraca: Data collection, Data analysis F Proietti: Data collection, Data analysis RS Flammia: Data collection, Data analysis S Guaglianone: Data collection, Data analysis R Lombardo: Data collection, Data analysis M Anselmi: Data collection, Data analysis A Zampa: Data collection, Data analysis C De Nunzio: Data collection, Data analysis AL Pastore: Data collection, Data analysis AB Galosi: Data collection, supervision C Leonardo: Data collection, supervision M Gallucci: Data collection, supervision G Simone: Manuscript editing, supervision Conflicts of interest: The authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript. Funding : This research received no external funding Institutional Review Board Statement: Not applicable Informed Consent Statement : Informed consent was obtained from all subjects involved in the study. Data Availability Statement: The data will be provided by authors under reasonable request. Author Contributions: Author Giuseppe Chiacchio and author Gabriele Tuderti have given substantial contributions to the conception of the manuscript, to acquisition, analysis and interpretation of the data. All authors have participated to collect data and drafting the manuscript. All authors read and approved the final version of the manuscript. References Roglic G (2016) WHO Global report on diabetes: A summary. International Journal of Noncommunicable Diseases 1(1):p 3–8, Apr–Jun 2016. | https://doi.org/10.4103/2468-8827.184853 GBD 2021 Diabetes Collaborators (2023) Global, regional, and. Lancet Lond Engl 402(10397):203–234. https://doi.org/10.1016/s0140-6736(23)01301-6 . national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021 Alfred Witjes J, Max Bruins H, Carrión A, Cathomas R, Compérat E, Efstathiou JA et al (2024) European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2023 Guidelines. Eur Urol 85(1):17–31. https://doi.org/10.1016/j.eururo.2023.08.016 Renehan A, Smith U, Kirkman MS (2010) Linking diabetes and cancer: a consensus on complexity. Lancet Lond Engl 375(9733):2201–2202. https://doi.org/10.1016/s0140-6736(10)60706-4 Cantiello F, Cicione A, Salonia A, Autorino R, De Nunzio C, Briganti A et al (2015) Association between metabolic syndrome, obesity, diabetes mellitus and oncological outcomes of bladder cancer: A systematic review. Int J Urol. 2015;22(1):22–32. https://doi.org/10.1111/iju.12644 Campbell PT, Newton CC, Patel AV, Jacobs EJ, Gapstur SM (2012) Diabetes and cause-specific mortality in a prospective cohort of one million U.S. adults. Diabetes Care. 2012;35(9):1835–44. https://doi.org/10.2337/dc12-0002 Chen Y, Wu F, Saito E, Lin Y, Song M, Luu HN et al (2017) Association between type 2 diabetes and risk of cancer mortality: a pooled analysis of over 771,000 individuals in the Asia Cohort Consortium. Diabetologia. 2017;60(6):1022–32. https://doi.org/10.1007/s00125-017-4229-z Xu Y, Huo R, Chen X, Yu X (2017) Diabetes mellitus and the risk of bladder cancer: A PRISMA-compliant meta-analysis of cohort studies. Medicine (Baltimore). 2017;96(46):e8588. https://doi.org/10.1097/md.0000000000008588 Hwang EC, Kim YJ, Hwang IS, Hwang JE, Jung SI, Kwon DD et al (2011) Impact of diabetes mellitus on recurrence and progression in patients with non-muscle invasive bladder carcinoma: a retrospective cohort study. Int J Urol Off J Jpn Urol Assoc. 2011;18(11):769–76. https://doi.org/10.1111/j.1442-2042.2011.02845.x Swerdlow AJ, Laing SP, Qiao Z, Slater SD, Burden AC, Botha JL et al (2005) Cancer incidence and mortality in patients with insulin-treated diabetes: a UK cohort study. Br J Cancer. 2005;92(11):2070–5. https://doi.org/10.1038/sj.bjc.6602611 Zendehdel K, Nyrén O, Ostenson C-G, Adami H-O, Ekbom A, Ye W (2003) Cancer incidence in patients with type 1 diabetes mellitus: a population-based cohort study in Sweden. J Natl Cancer Inst. 2003;95(23):1797–800. https://doi.org/10.1093/jnci/djg105 Simone G, Tuderti G, Misuraca L, Anceschi U, Ferriero M, Minisola F et al (2018) Perioperative and mid-term oncologic outcomes of robotic assisted radical cystectomy with totally intracorporeal neobladder: Results of a propensity score matched comparison with open cohort from a single-centre series. Eur J Surg Oncol J Eur Soc Surg Oncol Br Assoc Surg Oncol. 2018;44(9):1432–8. https://doi.org/10.1016/j.ejso.2018.04.006 Tuderti G, Mastroianni R, Brassetti A et al (2021) Robot-assisted radical cystectomy with intracorporeal neobladder: impact of learning curve and long-term assessment of functional outcomes. Minerva Urol Nephrol 2021; 73:754–62. https://doi.org/10.23736/s2724-6051.20.03948-x Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461–70. https://doi.org/10.7326/0003-4819-130-6-199903160-00002 Dindo D, Demartines N, Clavien P-A (2004) Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13. https://doi.org/10.1097/01.sla.0000133083.54934.ae Liu S, Li Y, Lin T, Fan X, Liang Y, Heemann U (2011) High dose human insulin and insulin glargine promote T24 bladder cancer cell proliferation via PI3K-independent activation of Akt. Diabetes Res Clin Pract. 2011;91(2):177–82. https://doi.org/10.1016/j.diabres.2010.11.009 Cantiello F, Cicione A, Salonia A, Autorino R, De Nunzio C, Briganti A et al (2015) Association between metabolic syndrome, obesity, diabetes mellitus and oncological outcomes of bladder cancer: A systematic review. Int J Urol. 2015;22(1):22–32. https://doi.org/10.1111/iju.12644 Coughlin SS, Calle EE, Teras LR, Petrelli J, Thun MJ (2004) Diabetes Mellitus as a Predictor of Cancer Mortality in a Large Cohort of US Adults. Am J Epidemiol. 2004;159(12):1160–7. https://doi.org/10.1093/aje/kwh161 Campbell PT, Newton CC, Patel AV, Jacobs EJ, Gapstur SM (2012) Diabetes and cause-specific mortality in a prospective cohort of one million U.S. adults. Diabetes Care. 2012;35(9):1835–44. https://doi.org/10.2337/dc12-0002 Rao Kondapally Seshasai S, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N et al (2011) Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829–41. https://doi.org/10.1056/nejmoa1008862 Zhu Z, Zhang X, Shen Z, Zhong S, Wang X, Lu Y et al (2013) Diabetes Mellitus and Risk of Bladder Cancer: A Meta-Analysis of Cohort Studies. PLoS ONE. 2013;8(2):e56662 https://doi.org/10.1371/journal.pone.0056662 Bochner BH, Dalbagni G, Marzouk KH et al (2018) Randomized Trial Comparing Open Radical Cystectomy and Robot-assisted Laparoscopic Radical Cystectomy: Oncologic Outcomes. Eur Urol 2018; 74:465–71. https://doi.org/10.1016/j.eururo.2018.04.030 Parekh DJ, Reis IM, Castle EP et al (2018) Robot-assisted radical cystectomy versus open radical cystectomy in patients with bladder cancer (RAZOR): an open-label, randomised, phase 3, non-inferiority trial. Lancet 2018; 391:2525–36. https://doi.org/10.1016/s0140-6736(18)30996-6 Mastroianni R, Tuderti G, Ferriero M et al (2023) Open versus robot-assisted radical cystectomy: pentafecta and trifecta achievement comparison from a randomised controlled trial. BJU Int. 2023; 132:671 – 77. https://doi.org/10.1111/bju.16134 Mastroianni R, Tuderti G, Ferriero M et al (2023) Open vs robotic intracorporeal Padua ileal bladder: functional outcomes of a single-centre RCT. World J Urol 2023; 41:739 – 46. https://doi.org/10.1007/s00345-023-04312-3 Mastroianni R, Tuderti G, Ferriero M et al (2024) Robot-assisted Radical Cystectomy with Totally Intracorporeal Urinary Diversion Versus Open Radical Cystectomy: 3-Year Outcomes from a Randomised Controlled Trial. Eur Urol 2024; 85: 422 – 30. https://doi.org/10.1016/j.eururo.2024.01.018 Brassetti A, Cacciamani G, Anceschi U et al (2020) Long-term oncologic outcomes of robot-assisted radical cystectomy (RARC) with totally intracorporeal urinary diversion (ICUD): a multi-center study. World J Urol 2020; 38:837–843. https://doi.org/10.1007/s00345-019-02842-3 Tuderti G, Mastroianni R, Chiacchio G, Anceschi U, Bove AM, Brassetti A, Ferriero M, Misuraca L, Flammia RS, Proietti F, D'Annunzio S, Leonardo C, Guaglianone S, Anselmi M, Zampa A, Galosi AB, Torregiani G, Gallucci M, Simone G (2023) Long-term oncologic and functional outcomes following robot-assisted radical cystectomy and intracorporeal Padua ileal bladder: results from a single high-volume center. World J Urol 2023; 41:2359–66. https://doi.org/10.1007/s00345-023-04523-8 Tuderti G, Mastroianni R, Anceschi U, Bove AM, Brassetti A, Ferriero M, Misuraca L, Flammia RS, Proietti F, D'Annunzio S, Leonardo C, Guaglianone S, Anselmi M, Zampa A, Torregiani G, Gallucci M, Simone G (2024) Learning curve for intracorporeal robotic Padua ileal bladder: 10-year functional assessment from a high-volume single-centre series BJU Int 2024; 134: 103–109 https://doi.org/10.1007/s00345-023-04523-8 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 May, 2024 Read the published version in Journal of Urology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4638244","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":326874922,"identity":"22336962-9100-44e1-883a-09cebad4b904","order_by":0,"name":"Gabriele Tuderti","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Gabriele","middleName":"","lastName":"Tuderti","suffix":""},{"id":326874923,"identity":"385ef946-0950-47aa-9dbc-0414997f8c20","order_by":1,"name":"Giuseppe Chiacchio","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYDACZgjFww8iEwpI0CIj2QDSYkCCZTYGB0AUMVrk3XkPPi7cYcNjfH514ocHBgzy/GIH8GsxPMyXbDzzTBqP2Y23myWADjOcOTuBgJZmHjNp3rbDQC1nN4C0JBjcJqzF/DdIi/GMs5t/EKVFnpnHjBmkxYC/dxtxthgw8yVLg/wicYN3m0WCgQRhv8j3nz34GRhi9vz9Zzff/FFhI88vTciWAzwMzIwNQJYEWKUEfuVgWxpgWvgPEFY9CkbBKBgFIxMAAPHWP/Ok6PWvAAAAAElFTkSuQmCC","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":true,"prefix":"","firstName":"Giuseppe","middleName":"","lastName":"Chiacchio","suffix":""},{"id":326874924,"identity":"f0e8035b-fbc9-4105-8698-ac16b25a5abf","order_by":2,"name":"Riccardo Mastroianni","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Riccardo","middleName":"","lastName":"Mastroianni","suffix":""},{"id":326874925,"identity":"3ab14436-2061-4db0-8e4d-55d3fa3a4abe","order_by":3,"name":"Umberto Anceschi","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Umberto","middleName":"","lastName":"Anceschi","suffix":""},{"id":326874926,"identity":"ba813d66-aa39-43b6-b3a3-c4383fe06587","order_by":4,"name":"Alfredo Maria Bove","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Alfredo","middleName":"Maria","lastName":"Bove","suffix":""},{"id":326874927,"identity":"398ecdb1-3130-46cc-bcf5-77d4e50e6af4","order_by":5,"name":"Aldo Brassetti","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Aldo","middleName":"","lastName":"Brassetti","suffix":""},{"id":326874928,"identity":"1eee8a4e-3c49-4b05-857d-a2259728f9d5","order_by":6,"name":"Simone D'Annunzio","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Simone","middleName":"","lastName":"D'Annunzio","suffix":""},{"id":326874929,"identity":"e7ad1647-fc49-4323-8dbd-b6da926e591f","order_by":7,"name":"Mariaconsiglia Ferriero","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Mariaconsiglia","middleName":"","lastName":"Ferriero","suffix":""},{"id":326874930,"identity":"31c6c6da-2b48-4558-97bc-daa2e25ee09d","order_by":8,"name":"Leonardo Misuraca","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Leonardo","middleName":"","lastName":"Misuraca","suffix":""},{"id":326874931,"identity":"2c984c54-3913-4178-b92f-570f6dd936af","order_by":9,"name":"Flavia Proietti","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Flavia","middleName":"","lastName":"Proietti","suffix":""},{"id":326874932,"identity":"fb945039-6a4a-4fb2-bba4-776d08919354","order_by":10,"name":"Rocco Simone Flammia","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Rocco","middleName":"Simone","lastName":"Flammia","suffix":""},{"id":326874933,"identity":"ab02b777-799b-4d4e-8c2d-3de9a34533c4","order_by":11,"name":"Salvatore Guaglianone","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Salvatore","middleName":"","lastName":"Guaglianone","suffix":""},{"id":326874934,"identity":"1a57d5a9-6545-4df5-ae8b-aeda882750f4","order_by":12,"name":"Riccardo Lombardo","email":"","orcid":"","institution":"“Sapienza” University of Rome-Ospedale Sant'Andrea","correspondingAuthor":false,"prefix":"","firstName":"Riccardo","middleName":"","lastName":"Lombardo","suffix":""},{"id":326874935,"identity":"a5750b4f-409d-4fc7-ba29-d763801b57b0","order_by":13,"name":"Marianna Anselmi","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Marianna","middleName":"","lastName":"Anselmi","suffix":""},{"id":326874936,"identity":"6e2ddd10-d443-4100-a37a-84b9f8e579d1","order_by":14,"name":"Ashanti Zampa","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Ashanti","middleName":"","lastName":"Zampa","suffix":""},{"id":326874937,"identity":"dc014258-9884-4491-8247-56240d6e3a06","order_by":15,"name":"CosimoDe Nunzio","email":"","orcid":"","institution":"“Sapienza” University of Rome-Ospedale Sant'Andrea","correspondingAuthor":false,"prefix":"","firstName":"CosimoDe","middleName":"","lastName":"Nunzio","suffix":""},{"id":326874938,"identity":"acbd210d-bde3-4f62-98eb-e3a448b0fed8","order_by":16,"name":"Antonio Luigi Pastore","email":"","orcid":"","institution":"“Sapienza” University of Rome -ICOT Latina Polo Pontino","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"Luigi","lastName":"Pastore","suffix":""},{"id":326874939,"identity":"a6de62a8-8b84-4684-8dc1-06756869bda7","order_by":17,"name":"Andrea Benedetto Galosi⁴","email":"","orcid":"","institution":"Azienda Ospedaliero-Universitaria delle Marche, Università Politecnica delle Marche","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Benedetto","lastName":"Galosi⁴","suffix":""},{"id":326874940,"identity":"0d1ff044-549e-4eef-9421-9519b6d10ad2","order_by":18,"name":"Costantino Leonardo","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Costantino","middleName":"","lastName":"Leonardo","suffix":""},{"id":326874941,"identity":"eb474620-3b1d-41c3-a6bc-7098b3f77664","order_by":19,"name":"Michele Gallucci","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Michele","middleName":"","lastName":"Gallucci","suffix":""},{"id":326874942,"identity":"68d4d8e2-0b62-450b-9f2b-fc875d5c6e9d","order_by":20,"name":"Giuseppe Simone","email":"","orcid":"","institution":"IRCCS \"Regina Elena\" National Cancer Institute","correspondingAuthor":false,"prefix":"","firstName":"Giuseppe","middleName":"","lastName":"Simone","suffix":""}],"badges":[],"createdAt":"2024-06-25 18:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4638244/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4638244/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1097/01.JU.0001009404.49693.12.02","type":"published","date":"2024-05-01T19:31:49+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60706360,"identity":"370c1f59-de9f-4fa4-b3c8-0e0a5e0c63c4","added_by":"auto","created_at":"2024-07-19 19:28:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":61439,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(1a,1b,1c): \u003c/strong\u003eKaplan-Meier analysis assessing DFS, CSS and OS probability over time between DM and Non-DM patients\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4638244/v1/4f8ecf41c919e6220e658075.png"},{"id":60707834,"identity":"43936f3f-43cc-4ab5-8fbc-9afb9b31eb5a","added_by":"auto","created_at":"2024-07-19 19:36:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":800391,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4638244/v1/b9f6b5cd-3f86-49a9-85e0-802e258a640a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of diabetes mellitus on oncologic outcomes in patients receiving robot- assisted radical cystectomy for bladder cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus (DM) represents a chronic metabolic disorder and constitutes a highly significant public health concern. Impacting millions of people globally, DM might be responsible of severe acute and chronic complications, such as hyperglycemia-induced damage to nerves and blood vessels, leading to conditions like neuropathy, nephropathy, and an increased risk of heart disease and stroke [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the International Diabetes Federation, the number of individuals living with DM has risen dramatically, from 180 millions in 1980 to an estimated 529\u0026nbsp;million in 2021 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]; these data translate to a global age-standardized prevalence of 6.1% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. On the other hand, Urothelial carcinoma of the bladder is a highly aggressive malignancy associated with substantial morbidity and mortality burdens [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In European countries, the age-standardized incidence rate is 20 per 100,000 individuals for men and 4.6 for women; furthermore, approximately 25% of patients diagnosed with bladder cancer (BC) present with muscle-invasive (MI) disease, which carries a poorer prognosis. At ten years, the disease-free survival (DFS) and overall survival (OS) rates for MIBC are 35% and 58%, respectively. Notably, the 5-yr OS rate plummets to only 18% for node-positive patients who undergo radical cystectomy (RC) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCompelling evidence suggests an association between DM and increased incidence and mortality from various cancers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As a matter of fact, several studies have revealed a link between DM and a rise in cancer incidence [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], along with a poorer prognosis in a range of malignancies [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], such as colorectal, breast, endometrial, liver, pancreatic, and bladder cancers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Focusing on BC, it has been fully assessed that DM represents an independent predictor of disease recurrence and progression-free survival in patients with MIBC who underwent open radical cystectomy (ORC) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, other studies have failed to establish a clear association between the two diseases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In the last decade, the technological advancements in BC treatment have witnessed a remarkable evolution, transitioning from open surgery to minimally invasive and robotic-assisted surgical approaches [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven the established prevalence of DM and its potential association with oncological outcomes in urothelial carcinoma, and considered the increasing adoption of robotic surgery in the treatment of MIBC, this multicenter retrospective study aims to investigate the impact of DM on cancer-related outcomes in patients with MI or high-risk non-muscle invasive (NMI) BC undergoing robot-assisted radical cystectomy (RARC).\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eAn IRB approved multi-institutional BC database was queried, including patients underwent RARC for MI or high-risk NMI BC in three high-volume centers between January 2013 and June 2023. Patients were divided into two groups according to DM status at the time of surgery. No type 1 DM patients were enrolled. We excluded patients who had metastasis at the time of RARC. Inclusion criteria were MI or recurrent high-grade urothelial NMIBC refractory to intravesical immunotherapy. Severe cardiovascular, respiratory or cognitive diseases, ejection fraction\u0026thinsp;\u0026lt;\u0026thinsp;36%, retinal vascular diseases, presence of ventriculo-peritoneal shunt and previous major bowel surgeries were contraindications for robotic surgery. After surgery, ERAS protocol was applied, consisting of immediate post-operative nasogastric tube removal, fluid intake since 1st post-operative day (POD), solid intake at first flatus; patient were stimulated to leave the bed early, encouraging to be seat at 1st POD and move for a soft walking at 2nd POD.\u003c/p\u003e \u003cp\u003eAll RARC procedures were performed by expert surgeons, which had already carried out several robotic procedures, in terms of prostate and renal surgery, and had also a large experience in open ORC. The surgical team is usually composed by the console surgeon, the bed-side assistant surgeon, a urology resident, and a bed-side nurse. The type of urinary diversion (neobladder, ileal conduit, ureterocutaneostomy or pouch) was decided according of the preoperative and intraoperative characteristics of the patients. Baseline demographic, clinical, perioperative, pathologic data were compared. Baseline and preoperative characteristics, including age, BMI, gender, hypertension, smoking status, American Society of Anesthesiologists (ASA) score, neoadjuvant chemotherapy (Neo-CHT), preoperative Haemoglobin (Hgb) and preoperative estimated glomerular filtration rate (eGFR) were systematically recorded. Renal function was evaluated using serum creatinine and eGFR, calculated using the Modification of Diet in Renal Disease (MDRD) formula [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePerioperative data consisted of type of urinary diversion, mean hospital stay, operative time, and perioperative complications rates, which were documented according to the Clavien\u0026ndash;Dindo (CD) classification system [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Major complications were defined by CD\u0026thinsp;\u0026ge;\u0026thinsp;3. Pathologic outcomes evaluated were pT stage, pN stage, lymph-node count, concomitant Cis and positive surgical margins (PSM) status.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eCategorical variables were described using frequencies and proportions. Continuous variables were reported using mean and standard deviation (SD). Chi-square and Student t tests were performed to compare categorical and continuous variables, respectively. The Kaplan-Meier method was performed to compare survival outcomes between the two cohorts of patients.\u003c/p\u003e \u003cp\u003eUnivariable and multivariable Cox regression analysis were used to identify independent predictors of DFS, cancer-specific survival (CSS) and OS. The significance level was set at \u0026lt;\u0026thinsp;0.05. All tests were two-sided, and statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS v.21, IBM Corp., Armonk, NY, USA) and with the R statistical package (v.2.14.2)\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"387\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients, n\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-DM (450)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM (97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eAge, yr, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e65.8 (\u0026plusmn; 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\"\u003e\n \u003cp\u003e67.9 (\u0026plusmn; 11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eBMI, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e26.1 (\u0026plusmn; 7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e26 (\u0026plusmn; 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eMale gender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e354 (78.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e79 (81.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eSmoking, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e337 (74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e74 (76.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e224 (49.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e68 (70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eASA score, n(%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22 (4.9)\u003c/p\u003e\n \u003cp\u003e302 (67.1)\u003c/p\u003e\n \u003cp\u003e120 (26.7)\u003c/p\u003e\n \u003cp\u003e6 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2 (2.1)\u003c/p\u003e\n \u003cp\u003e52 (53.6)\u003c/p\u003e\n \u003cp\u003e40 (41.2)\u003c/p\u003e\n \u003cp\u003e3 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003eNeoadjuvant CHT, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e119 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e16 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003ePreoperative Hgb, g/dl, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12.9 (\u0026plusmn; 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12.9 (\u0026plusmn; 1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.02061855670103%\"\u003e\n \u003cp\u003ePreoperative eGFR, ml/min, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e66 (\u0026plusmn; 37.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.484536082474225%\"\u003e\n \u003cp\u003e58.5 (\u0026plusmn; 37.4)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.690721649484535%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Baseline and preoperative characteristics\u003c/p\u003e\n\u003cp\u003eOut of 547 consecutive patients included in the study, 97 (17.7%) had DM. DM patients displayed a significantly higher rate of hypertension (70.1 % vs 49.8%, p \u0026lt;0.001) and comorbidities (ASA score \u0026sup3; 3: 44.3% vs 28 %, p=0.01) (Table 1). Perioperative and pathologic data were reported in Table 2. Urinary diversion types were equally distributed in the two cohorts, with intracorporeal orthotopic neobladder (ION) being the most adopted diversions in both groups (No-DM 55.6% vs DM 43.3%, p= 0.20). There were no significant differences between the two groups in terms of length of mean hospital stay (No-DM 8.7 days vs DM 8.8 days, p=0.99) and mean operative time (No-DM 273.5 mins vs DM 269.3 mins, p=0.69). The two groups showed comparable overall perioperative complications rates (No-DM 42.1% vs DM 39.6%, p=0.72), as well as severe (Clavien grade \u0026gt; 2) complications rates (No-DM 8.2% vs DM 8.2%, p=1). No differences were detected in terms pT stage, pN stage and PSM status (all p\u0026gt;0.12). The mean lymph-node count was 27.1 vs 24.4 in No-DM and DM group, respectively (p=0.08). Concomitant Cis was reported in 150 (33.4%) pts in the No-DM group and in 35 (36.2%) pts in the DM group (p 0.63). (Table2.). \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"500\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients, n\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-DM (450)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM (97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eType of urinary diversion, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Neobladder\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Ileal conduit\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Ureterocutaneostomy\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Pouch\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e250 (55.6)\u003c/p\u003e\n \u003cp\u003e94 (20.9)\u003c/p\u003e\n \u003cp\u003e102 (22.6)\u003c/p\u003e\n \u003cp\u003e4 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42 (43.3)\u003c/p\u003e\n \u003cp\u003e24 (24.7)\u003c/p\u003e\n \u003cp\u003e29 (29.9)\u003c/p\u003e\n \u003cp\u003e2 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eHospital stay, days, mean (\u0026plusmn;\u0026nbsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e8.7 (\u0026plusmn;\u0026nbsp;8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e8.8 (\u0026plusmn;\u0026nbsp;11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eOperative time, min, mean (\u0026plusmn;\u0026nbsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e273.5 (\u0026plusmn;\u0026nbsp;95.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e269.3 (\u0026plusmn;\u0026nbsp;97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\" valign=\"top\"\u003e\n \u003cp\u003eOverall Perioperative complications, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e189 (42.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e38 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\" valign=\"top\"\u003e\n \u003cp\u003eClavien 1-2 perioperative complications, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e174 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e35 (36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\" valign=\"top\"\u003e\n \u003cp\u003eClavien \u0026nbsp;3 perioperative complications, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e37 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e8 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003epT stage, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0, a\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;is\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e114 (25.4)\u003c/p\u003e\n \u003cp\u003e46 (10.3)\u003c/p\u003e\n \u003cp\u003e37 (8.2)\u003c/p\u003e\n \u003cp\u003e76 (16.7)\u003c/p\u003e\n \u003cp\u003e117 (26.1)\u003c/p\u003e\n \u003cp\u003e60 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (21.3)\u003c/p\u003e\n \u003cp\u003e5 (5.3)\u003c/p\u003e\n \u003cp\u003e4 (4.3)\u003c/p\u003e\n \u003cp\u003e26 (26.6)\u003c/p\u003e\n \u003cp\u003e28 (28.7)\u003c/p\u003e\n \u003cp\u003e13(13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003epN stage, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e355 (78.8)\u003c/p\u003e\n \u003cp\u003e26 (6)\u003c/p\u003e\n \u003cp\u003e59 (13)\u003c/p\u003e\n \u003cp\u003e10 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e72 (74.4)\u003c/p\u003e\n \u003cp\u003e9 (8.9)\u003c/p\u003e\n \u003cp\u003e11 (11.1)\u003c/p\u003e\n \u003cp\u003e5 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eLymph-node count, mean (\u0026plusmn;\u0026nbsp;SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e27.1 (\u0026plusmn;\u0026nbsp;12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e24.4 (\u0026plusmn;\u0026nbsp;10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eConcomitant Cis, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e150 (33.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e35 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003ePositive surgical margins, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e12 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53.8%\"\u003e\n \u003cp\u003eFollow-up, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.4%\"\u003e\n \u003cp\u003e31.3 (\u0026plusmn;\u0026nbsp;31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.8%\"\u003e\n \u003cp\u003e20.8 (\u0026plusmn;\u0026nbsp;24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. Perioperative and pathologic outcomes\u003c/p\u003e\n\u003cp\u003eWith reference to survival analysis, DM patients displayed a statistically significantly lower DFS (5-yr: 44.6% vs 63.3%, p=0.007), CSS (5-yr: 45.1% vs 70.1%, p=0.001) and OS (5-yr: 39.9% vs 63.8%, p=0.001) (Fig 1a-1b-1c).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt Multivariable Cox-regression analyses, after adjustment for other covariates acknowledged for impacting on survival outcomes, DM status was identified as an independent predictor of lower CSS (HR 2.1, 95% CI 1.35-3.24; p=0.001; Table 3a) and lower OS (HR 2.05, 95% CI 1.43-2.96; p\u0026lt;0.001; Table 3b) but not of lower DFS (HR 1.43, 95% CI 0.94-2.18; p 0.08; Table 3c).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1(1a,1b,1c):\u0026nbsp;\u003c/strong\u003eKaplan-Meier analysis assessing DFS, CSS and OS probability over time between DM and Non-DM patients\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"A table with numbers and tablesDescription automatically generated with medium confidence\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 (3a, 3b,3c)\u0026nbsp;\u003c/strong\u003eUnivariable and multivariable cox regression analyses to identify independent predictors of CSS, OS and DFS\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSeveral studies have established an association between DM and an increased cancer incidence and poorer prognosis across various malignancies, including colorectal, breast, endometrial, liver, pancreatic, and BC [\u003cspan additionalcitationids=\"CR5 CR6 CR7\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The precise nature of this association remains under investigation. While some propose a direct causal relationship mediated by hyperinsulinemia and poor glycemic control [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], others suggest an indirect association driven by shared risk factors, among which one of the principal ones is obesity [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe crucial role that DM might play in worsening survival outcomes was initially debated about twenty years ago, when Coughlin et al. performed a prospective study, evaluating one million of American patients for a long-time period of 16 years, and identified DM as an independent risk factor for cancer specific mortality (CSM) in men (RR 1.43, 95% CI 1.14\u0026ndash;1.80) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similar findings were reported by Campbell et al., in a study with a median follow up of 26 years, showing that the risk of death in DM male patients with BC was superior (RR 1.22, 95% CI 1.01\u0026ndash;1.47) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, such association between DM and BC was highlighted in another multi-center study, in which the authors observed a positive correlation between DM and BC mortality, with higher fasting blood glucose levels associated with a greater risk of death [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Moreover, Zhu et al, in a cumulative meta-analysis, displayed a negative impact on BC mortality in DM men patients (RR 1.55, 95% CI 1.30\u0026ndash;1.82) but also in DM female ones (RR 1.50, 95% CI 1.05\u0026ndash;2.14) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the last decade, evidence supporting a negative impact of DM on oncologic outcomes in patients undergoing extirpative surgery for BC have been accumulating, with several data deriving from large cohorts studies. Accordingly, in a more recent meta-analysis, Xu et al. included and analyzed 21 cohorts studies, involving 13 millions participants, and reported that DM was associated with a higher risk of BC and cancer mortality (HR: 1.23; 95% CI 1.12\u0026ndash;1.35) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003eThese results are in agreement with a systematic review conducted by Cantiello et al., where the effects of various comorbidities, such as smoking status, hypertension, obesity, and DM, on oncologic outcomes of BC were analyzed and well-established [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll the literature examining the relationship between DM and BC often refer to series in which patients were treated through an open approach, thus before the wide-spread diffusion and consequent adoption of robotic surgery for BC.\u003c/p\u003e \u003cp\u003eAs a matter of fact, although the open approach was the most widely adopted worldwide for several years, RARC has gained increasing popularity over the past decade. This is due to the potential benefits of a minimally invasive approach, such as lower morbidity, shorter hospital stays (LOS), and quicker patient recovery. The oncological effectiveness of RARC has been extensively studied, and its equivalence to ORC has been confirmed in recent randomized controlled trials (RCTs) [\u003cspan additionalcitationids=\"CR23 CR24 CR25\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In addition, long-term survival data of RARC have been adequately addressed in high-volume multicenter series, providing survival rates aligned with the largest open series [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccordingly, a recent single center retrospective study including RARC-ICUD patients, reported long-term oncologic data, reinforcing the oncologic effectiveness of robotic approach (5-yr DFS 66.5%, 5-ys CSS 65.4%, 5-yr OS 61.5%) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHaving established the equivalence in terms of oncologic outcomes between the surgical approaches, our study investigated the impact of diabetes mellitus (DM) on oncological outcomes in patients with muscle-invasive or high-risk non-muscle invasive bladder cancer (BC) undergoing RARC.\u003c/p\u003e \u003cp\u003eBy analyzing our results, patients with DM had demonstrated to have worse oncologic outcomes, showing a 5-yr DFS significantly lower than patients without DM (44.6% vs 63.3%, log-rank p\u0026thinsp;=\u0026thinsp;0.007). DM cohort displayed also significantly lower 5-yr CSS (45.1% vs 70.1%, log-rank p\u0026thinsp;=\u0026thinsp;0.001) and 5-yr OS (39.9% vs 63.8%, log-rank p\u0026thinsp;=\u0026thinsp;0.001). In corroboration of these findings, at Cox- regression MV analysis, DM has been shown to be a significant predictor of CSS, providing a 2.1-fold increased risk of cancer-related mortality (HR\u0026thinsp;=\u0026thinsp;2.1, 95% CI 1.35\u0026ndash;3.24, p\u0026thinsp;=\u0026thinsp;0.001), and OS, providing a 2.05-fold increased risk of all-cause mortality (HR\u0026thinsp;=\u0026thinsp;2.05, 95% CI 1.43\u0026ndash;2.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The present paper is not devoid of limitations. Firstly, its retrospective design and a relatively small cohort, particularly regarding patients with DM, restrict our ability to analyze potentially significant factors like lymphovascular invasion, mixed histologic variants, and medication use (aspirin, statins). Secondly, the unassessed duration of DM introduces potential recall bias and the possibility of undetected cases. Thirdly, we did not analyze the potential differences in outcomes between DM patients receiving metformin and those not receiving it. Finally, the high-volume caseload of the centers and the need for advanced robotic surgical expertise [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] might affect the reproducibility of these outcomes in daily practice.\u003c/p\u003e \u003cp\u003eDespite these limitations, our study contributes valuable insights to the limited existing literature exploring the association between DM and oncological outcomes in BC patients undergoing RARC. These findings may guide future research and clinical practice for managing urothelial carcinoma patients with DM in the era of robotic surgery.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study indicates that among BC patients who underwent RARC, those with DM experienced significantly worse oncological outcomes. DM status appears to be an independent negative predictor for both CSS and OS, providing a 2-fold increased risk of cancer-related and all-cause mortality. These findings warrant further validation through prospective studies. Additionally, focused investigations, both basic and translational, are awaited in order to uncover the biological mechanisms driving the interaction between DM and worsened BC outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eG Tuderti: project development, Manuscript editing Data analysis\u003c/p\u003e\n\u003cp\u003eG Chiacchio:\u0026nbsp;Manuscript writing, Data analysis\u003c/p\u003e\n\u003cp\u003eRMastroianni: Data analysis\u003c/p\u003e\n\u003cp\u003eU Anceschi: Manuscript editing\u003c/p\u003e\n\u003cp\u003eAM Bove: Data analysis, Manuscript editing\u003c/p\u003e\n\u003cp\u003eA Brassetti: Data analysis, Manuscript editing\u003c/p\u003e\n\u003cp\u003eS D\u0026apos;Annunzio: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eM Ferriero: Manuscript writing/editing, Data analysis\u003c/p\u003e\n\u003cp\u003eL Misuraca: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eF Proietti:\u0026nbsp;Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eRS Flammia: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eS Guaglianone: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eR Lombardo: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eM Anselmi: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eA Zampa: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eC De Nunzio: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eAL \u0026nbsp;Pastore: Data collection, Data analysis\u003c/p\u003e\n\u003cp\u003eAB Galosi: Data collection, supervision\u003c/p\u003e\n\u003cp\u003eC Leonardo: Data collection, supervision\u003c/p\u003e\n\u003cp\u003eM Gallucci: Data collection, supervision\u003c/p\u003e\n\u003cp\u003eG Simone: Manuscript editing, supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflicts of interest:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e: This research received no external funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInformed Consent Statement\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003eInformed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Availability Statement:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe data will be provided by authors under reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributions:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAuthor Giuseppe Chiacchio and author Gabriele Tuderti have given substantial contributions to the conception of the manuscript, to acquisition, analysis and interpretation of the data. All authors have participated to collect data and drafting the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRoglic G (2016) WHO Global report on diabetes: A summary. International Journal of Noncommunicable Diseases 1(1):p 3\u0026ndash;8, Apr\u0026ndash;Jun 2016. | \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/2468-8827.184853\u003c/span\u003e\u003cspan address=\"10.4103/2468-8827.184853\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGBD 2021 Diabetes Collaborators (2023) Global, regional, and. Lancet Lond Engl 402(10397):203\u0026ndash;234. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s0140-6736(23)01301-6\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(23)01301-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlfred Witjes J, Max Bruins H, Carri\u0026oacute;n A, Cathomas R, Comp\u0026eacute;rat E, Efstathiou JA et al (2024) European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2023 Guidelines. Eur Urol 85(1):17\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eururo.2023.08.016\u003c/span\u003e\u003cspan address=\"10.1016/j.eururo.2023.08.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRenehan A, Smith U, Kirkman MS (2010) Linking diabetes and cancer: a consensus on complexity. Lancet Lond Engl 375(9733):2201\u0026ndash;2202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s0140-6736(10)60706-4\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(10)60706-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantiello F, Cicione A, Salonia A, Autorino R, De Nunzio C, Briganti A et al (2015) Association between metabolic syndrome, obesity, diabetes mellitus and oncological outcomes of bladder cancer: A systematic review. Int J Urol. 2015;22(1):22\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/iju.12644\u003c/span\u003e\u003cspan address=\"10.1111/iju.12644\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell PT, Newton CC, Patel AV, Jacobs EJ, Gapstur SM (2012) Diabetes and cause-specific mortality in a prospective cohort of one million U.S. adults. Diabetes Care. 2012;35(9):1835\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2337/dc12-0002\u003c/span\u003e\u003cspan address=\"10.2337/dc12-0002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Wu F, Saito E, Lin Y, Song M, Luu HN et al (2017) Association between type 2 diabetes and risk of cancer mortality: a pooled analysis of over 771,000 individuals in the Asia Cohort Consortium. Diabetologia. 2017;60(6):1022\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00125-017-4229-z\u003c/span\u003e\u003cspan address=\"10.1007/s00125-017-4229-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Huo R, Chen X, Yu X (2017) Diabetes mellitus and the risk of bladder cancer: A PRISMA-compliant meta-analysis of cohort studies. Medicine (Baltimore). 2017;96(46):e8588. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/md.0000000000008588\u003c/span\u003e\u003cspan address=\"10.1097/md.0000000000008588\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHwang EC, Kim YJ, Hwang IS, Hwang JE, Jung SI, Kwon DD et al (2011) Impact of diabetes mellitus on recurrence and progression in patients with non-muscle invasive bladder carcinoma: a retrospective cohort study. Int J Urol Off J Jpn Urol Assoc. 2011;18(11):769\u0026ndash;76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1442-2042.2011.02845.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1442-2042.2011.02845.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSwerdlow AJ, Laing SP, Qiao Z, Slater SD, Burden AC, Botha JL et al (2005) Cancer incidence and mortality in patients with insulin-treated diabetes: a UK cohort study. Br J Cancer. 2005;92(11):2070\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/sj.bjc.6602611\u003c/span\u003e\u003cspan address=\"10.1038/sj.bjc.6602611\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZendehdel K, Nyr\u0026eacute;n O, Ostenson C-G, Adami H-O, Ekbom A, Ye W (2003) Cancer incidence in patients with type 1 diabetes mellitus: a population-based cohort study in Sweden. J Natl Cancer Inst. 2003;95(23):1797\u0026ndash;800. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jnci/djg105\u003c/span\u003e\u003cspan address=\"10.1093/jnci/djg105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimone G, Tuderti G, Misuraca L, Anceschi U, Ferriero M, Minisola F et al (2018) Perioperative and mid-term oncologic outcomes of robotic assisted radical cystectomy with totally intracorporeal neobladder: Results of a propensity score matched comparison with open cohort from a single-centre series. Eur J Surg Oncol J Eur Soc Surg Oncol Br Assoc Surg Oncol. 2018;44(9):1432\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejso.2018.04.006\u003c/span\u003e\u003cspan address=\"10.1016/j.ejso.2018.04.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuderti G, Mastroianni R, Brassetti A et al (2021) Robot-assisted radical cystectomy with intracorporeal neobladder: impact of learning curve and long-term assessment of functional outcomes. Minerva Urol Nephrol 2021; 73:754\u0026ndash;62. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.23736/s2724-6051.20.03948-x\u003c/span\u003e\u003cspan address=\"10.23736/s2724-6051.20.03948-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7326/0003-4819-130-6-199903160-00002\u003c/span\u003e\u003cspan address=\"10.7326/0003-4819-130-6-199903160-00002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDindo D, Demartines N, Clavien P-A (2004) Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/01.sla.0000133083.54934.ae\u003c/span\u003e\u003cspan address=\"10.1097/01.sla.0000133083.54934.ae\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Li Y, Lin T, Fan X, Liang Y, Heemann U (2011) High dose human insulin and insulin glargine promote T24 bladder cancer cell proliferation via PI3K-independent activation of Akt. Diabetes Res Clin Pract. 2011;91(2):177\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.diabres.2010.11.009\u003c/span\u003e\u003cspan address=\"10.1016/j.diabres.2010.11.009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCantiello F, Cicione A, Salonia A, Autorino R, De Nunzio C, Briganti A et al (2015) Association between metabolic syndrome, obesity, diabetes mellitus and oncological outcomes of bladder cancer: A systematic review. Int J Urol. 2015;22(1):22\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/iju.12644\u003c/span\u003e\u003cspan address=\"10.1111/iju.12644\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoughlin SS, Calle EE, Teras LR, Petrelli J, Thun MJ (2004) Diabetes Mellitus as a Predictor of Cancer Mortality in a Large Cohort of US Adults. Am J Epidemiol. 2004;159(12):1160\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/aje/kwh161\u003c/span\u003e\u003cspan address=\"10.1093/aje/kwh161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell PT, Newton CC, Patel AV, Jacobs EJ, Gapstur SM (2012) Diabetes and cause-specific mortality in a prospective cohort of one million U.S. adults. Diabetes Care. 2012;35(9):1835\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2337/dc12-0002\u003c/span\u003e\u003cspan address=\"10.2337/dc12-0002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao Kondapally Seshasai S, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N et al (2011) Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1056/nejmoa1008862\u003c/span\u003e\u003cspan address=\"10.1056/nejmoa1008862\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Z, Zhang X, Shen Z, Zhong S, Wang X, Lu Y et al (2013) Diabetes Mellitus and Risk of Bladder Cancer: A Meta-Analysis of Cohort Studies. PLoS ONE. 2013;8(2):e56662 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0056662\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0056662\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBochner BH, Dalbagni G, Marzouk KH et al (2018) Randomized Trial Comparing Open Radical Cystectomy and Robot-assisted Laparoscopic Radical Cystectomy: Oncologic Outcomes. Eur Urol 2018; 74:465\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eururo.2018.04.030\u003c/span\u003e\u003cspan address=\"10.1016/j.eururo.2018.04.030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParekh DJ, Reis IM, Castle EP et al (2018) Robot-assisted radical cystectomy versus open radical cystectomy in patients with bladder cancer (RAZOR): an open-label, randomised, phase 3, non-inferiority trial. Lancet 2018; 391:2525\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s0140-6736(18)30996-6\u003c/span\u003e\u003cspan address=\"10.1016/s0140-6736(18)30996-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMastroianni R, Tuderti G, Ferriero M et al (2023) Open versus robot-assisted radical cystectomy: pentafecta and trifecta achievement comparison from a randomised controlled trial. BJU Int. 2023; 132:671\u0026thinsp;\u0026ndash;\u0026thinsp;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/bju.16134\u003c/span\u003e\u003cspan address=\"10.1111/bju.16134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMastroianni R, Tuderti G, Ferriero M et al (2023) Open vs robotic intracorporeal Padua ileal bladder: functional outcomes of a single-centre RCT. World J Urol 2023; 41:739\u0026thinsp;\u0026ndash;\u0026thinsp;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00345-023-04312-3\u003c/span\u003e\u003cspan address=\"10.1007/s00345-023-04312-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMastroianni R, Tuderti G, Ferriero M et al (2024) Robot-assisted Radical Cystectomy with Totally Intracorporeal Urinary Diversion Versus Open Radical Cystectomy: 3-Year Outcomes from a Randomised Controlled Trial. Eur Urol 2024; 85: 422\u0026thinsp;\u0026ndash;\u0026thinsp;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.eururo.2024.01.018\u003c/span\u003e\u003cspan address=\"10.1016/j.eururo.2024.01.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrassetti A, Cacciamani G, Anceschi U et al (2020) Long-term oncologic outcomes of robot-assisted radical cystectomy (RARC) with totally intracorporeal urinary diversion (ICUD): a multi-center study. World J Urol 2020; 38:837\u0026ndash;843. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00345-019-02842-3\u003c/span\u003e\u003cspan address=\"10.1007/s00345-019-02842-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuderti G, Mastroianni R, Chiacchio G, Anceschi U, Bove AM, Brassetti A, Ferriero M, Misuraca L, Flammia RS, Proietti F, D'Annunzio S, Leonardo C, Guaglianone S, Anselmi M, Zampa A, Galosi AB, Torregiani G, Gallucci M, Simone G (2023) Long-term oncologic and functional outcomes following robot-assisted radical cystectomy and intracorporeal Padua ileal bladder: results from a single high-volume center. World J Urol 2023; 41:2359\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00345-023-04523-8\u003c/span\u003e\u003cspan address=\"10.1007/s00345-023-04523-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuderti G, Mastroianni R, Anceschi U, Bove AM, Brassetti A, Ferriero M, Misuraca L, Flammia RS, Proietti F, D'Annunzio S, Leonardo C, Guaglianone S, Anselmi M, Zampa A, Torregiani G, Gallucci M, Simone G (2024) Learning curve for intracorporeal robotic Padua ileal bladder: 10-year functional assessment from a high-volume single-centre series BJU Int 2024; 134: 103\u0026ndash;109 \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00345-023-04523-8\u003c/span\u003e\u003cspan address=\"10.1007/s00345-023-04523-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bladder cancer, Diabetes mellitus, Oncologic outcomes, Radical cystectomy, Robotic","lastPublishedDoi":"10.21203/rs.3.rs-4638244/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4638244/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePurpose\u003c/p\u003e\n\u003cp\u003eAim of this study is to investigate the association between DM and oncological outcomes among patients with muscle-invasive (MI) or high-risk non-muscle invasive (NMI) bladder cancer (BC) who underwent robot-assisted radical cystectomy with intracorporeal urinary diversion (RARC)\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eAn IRB approved multi-institutional BC database was queried, including patients underwent RARC between January 2013 and June 2023. Patients were divided into two groups according to DM status. Baseline, clinical, perioperative, pathologic data were compared. Chi-square and Student t tests were performed to compare categorical and continuous variables, respectively. Kaplan-Meier method and Cox regression analyses were performed to assess the association between DM and oncologic outcomes.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eOut of 547 consecutive patients, 97 (17.7%) had DM. The two cohorts showed similar preoperative features, except for ASA score (p=0.01) and Hypertension rates (p\u0026lt;0.001). No differences were detected for perioperative complications, pT stage, pN stages and surgical margins status (all p\u0026gt;0.12). DM patients displayed significantly lower 5-yr disease-free survival (DFS) (44.6% vs 63.3%, p=0.007), 5-yr cancer-specific survival (CSS) (45.1% vs 70.1%, p=0.001) and 5-yr Overall survival (OS) (39.9% vs 63.8%, p=0.001). At Multivariable Cox-regression analyses DM status was identified as independent predictor of worse cancer-specific survival (CSS) (HR 2.1; p=0.001) and overall survival (OS) (HR 2.05; p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eConclusion\u003c/p\u003e\n\u003cp\u003eAmong BC patients who underwent RARC, DM patients showed worse oncologic outcomes than the non-DM patients, with DM status playing an independent negative predicting role in CSS and OS. Future prospective studies are awaited, stimulating basic and translational research to identify possible mechanisms of interaction between DM and BC.\u003c/p\u003e","manuscriptTitle":"Impact of diabetes mellitus on oncologic outcomes in patients receiving robot- assisted radical cystectomy for bladder cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 19:28:31","doi":"10.21203/rs.3.rs-4638244/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23d79de9-addb-4256-a026-a0adb3261846","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-07-19T19:31:49+00:00","versionOfRecord":{"articleIdentity":"rs-4638244","link":"https://doi.org/10.1097/01.JU.0001009404.49693.12.02","journal":{"identity":"journal-of-urology","isVorOnly":true,"title":"Journal of Urology"},"publishedOn":"2024-05-01 19:31:49","publishedOnDateReadable":"May 1st, 2024"},"versionCreatedAt":"2024-07-19 19:28:31","video":"","vorDoi":"10.1097/01.JU.0001009404.49693.12.02","vorDoiUrl":"https://doi.org/10.1097/01.JU.0001009404.49693.12.02","workflowStages":[]},"version":"v1","identity":"rs-4638244","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4638244","identity":"rs-4638244","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}