Stesura Seveso 291Archivio Italiano di Urologia e Andrologia 2021; 93, 3 ORIGINAL PAPER No conflict of interest declared. INTRODUCTION Metabolic syndrome (MetS) is a clinical entity consisting of a cluster of hyperglycemia/insulin resistance, obesity, dyslipidemia and hypertension (1). MetS is documented as a traditional risk factor for atherosclerotic cardiovascu- lar disease (1, 2) and has become a global health problem with increasing prevalence, paralleling the increasing incidence of obesity and poor eating habits (3). It is well known that overweight and obese men are at increased risk of prostate enlargement and erectile dysfunction (4). Furthermore, there is accumulating evidence that meta- bolic syndrome is associated with some common forms of cancer, as well as it poses a negative impact on cancer morbidity and mortality (5). This association sounds rea- sonable, since obesity, diabetes, and dyslipidemia have already been shown to be interrelated with some forms of cancer (6-8). Nowadays, prostate cancer (PCa) is the second most com- mon male malignancy worldwide with established risk factors being increasing age, ethnic origin, and heredity (9). Association between PCa and MetS comprise a mat- ter of debate among published literature. Data suggest that single components of MetS, such as hypertension and central obesity, are related with a significantly greater risk of PCa (10). In contrast, patients suffering from > 3 components of MetS are found to have a reduced risk for PCa (11). The purpose of this study is to evaluate whether MetS correlates with PCa diagnosis and Gleason score (GS), in a sample of Greek patients who underwent prostate biopsy in a tertiary, high volume, PCa center. MATERIALS AND METHODS Study design Clinical data were collected from a prospective database in a tertiary PCa center, from consecutive patients who underwent transrectal, ultrasound-guided prostate biopsy between 2018-2019. Patients were eligible for inclusion Introduction and objective: Even though the only established risk factors for prostate cancer (PCa) are age, ethnic origin and family history, there are data suggesting that environmental factors, such as the presence of metabolic syndrome (MetS), may also play a role in the etiology of the disease. The aim of this study is to correlate MetS with PCa diagnosis and Gleason score (GS) in patients undergoing transrectal ultrasound guided prostate biopsy. Materials and methods: This is a prospective, single-center study including 378 patients who underwent transrectal ultra- sound guided prostate biopsy in our department during the years from 2018 to 2019. Patients were divided into two groups according to the presence of PCa. Group A included 197 patients diagnosed with PCa while Group B consisted of 181 patients without PCa in their biopsy result. Multiple vari- ables such as the presence of MetS and its components were evaluated in correlation to the presence of PCa and PCa char- acteristics. Statistical analysis was performed using the IBM SPSS Statistics v.23 program. Results: Mean PSA value was 8.7 ng/dl in the PCa group and 7.1 ng/dl in the non PCa group, respectively. MetS was diag- nosed in 108 patients (54.8%) with PCa and 80 patients (44.2%) without PCa and the difference was statistically signif- icant. Hypertriglyceridemia was the MetS component with sta- tistically higher frequency in PCa patients. Furthermore, the prevalence of MetS was higher in higher Gleason score PCa (GS ≥ 4+3) patients vs lower Gleason score PCa (GS ≤ 3+4) patients. More specifically, MetS, hypertriglyceridemia, and low HDL levels were independent factors associated with high- er Gleason score PCa (GS ≥ 4+3). Conclusions: Patients suffering from MetS who undergo prostate biopsy present with higher rates of PCa diagnosis and higher GS in comparison with patients with a normal metabolic profile. KEy wORDS: Metabolic syndrome; Prostate cancer; Association of metabolic syndrome with prostate cancer; Metabolic syndrome and prostate cancer characteristics; Metabolic syndrome and high Gleason score prostate cancer. Submitted 17 June 2021; Accepted 10 July 2021 Association of metabolic syndrome with prostate cancer diagnosis and aggressiveness in patients undergoing transrectal prostate biopsy Charalampos Fragkoulis 1, Ioannis Glykas 1, Lazaros Tzelves 2, Konstantinos Stasinopoulos 3, Lazaros Lazarou 2, Andreas Kaoukis 4, Athanasios Dellis 5, Georgios Stathouros 1, Georgios Papadopoulos 1, Konstantinos Ntoumas 1 1 Department of Urology, General Hospital of Athens ‘’G. Gennimatas’’, Athens, Greece; 2 2nd Department of Urology, National and Kapodistrian University of Athens, School of Medicine, Sismanoglio Hospital, Athens, Greece; 3 Department of Urology, General Hospital of Lakonia, Sparta, Greece; 4 Department of Cardiology, General Hospital of Athens ‘’G. Gennimatas’’, Athens, Greece; 5 2nd Department of Surgery, Aretaieion Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece. DOI: 10.4081/aiua.2021.3.291 Summary Archivio Italiano di Urologia e Andrologia 2021; 93, 3 C. Fragkoulis, I. Glykas, L. Tzelves, K. Stasinopoulos, L. Lazarou, A. Kaoukis, A. Dellis, G. Stathouros, G. Papadopoulos, K. Ntoumas 292 when there was a clinical suspicion for PCa, based on ele- vated total PSA values (> 4 ng/ml) or increasing trends of PSA values compared to previous results. A multiparamet- ric magnetic resonance imaging (mpMRI) was not an essen- tial component of our diagnostic algorithm, but when performed, reports indicating PIRADS 4 or 5 lesions, were an absolute indication to perform a biopsy. Patients presenting with PSA values > 20 ng/ml or signs suggestive of metastatic disease, were excluded. Biopsy technique The protocol for transrectal biopsy in our center uses the systematic approach, with 6 cores from each prostatic lobe in biopsy-naïve patients. In case images from a mpMRI were available, we also tar- geted suspicious lesions (cognitive biopsy), but no fusion protocol was followed. Patients received orally antibiotic prophylaxis two days before and two days after biopsy. Assessment of metabolic syndrome parameters Diagnosis of metabolic syndrome was based on the American Heart Association criteria (1). A patient suffer- ing from metabolic syndrome should present with three or more of the following five criteria: a) fasting glucose level ≥ 100 mg/dl (or prescription for treatment of dia- betes mellitus), b) blood pressure ≥ 130/85 mmHg (or prescription for treatment of hypertension), c) triglyc- erides levels ≥ 150 mg/dl (or prescription for treatment of hypertriglyceridemia), d) HDL cholesterol level < 40 mg/dl and e) central obesity, defined as a waist circum- ference ≥ 102 cm (Table 1). Patients were asked regard- ing the use of drug regimen for management of diabetes, hypertension, and hypertriglyceridemia and in those patients, who did not follow any prescription, we meas- ured fasting blood glucose levels and triglyceride levels. To assess hypertension, we performed blood pressure measurements at least on three occasions and also asked patients to present with a diary of measurements (three times daily for a week). In case abnormal blood pressure measurements were noted, a cardiology referral was made, and patient was considered to suffer from hyper- tension. We measured the waist circumference at our center using a scaled tape at the level above umbilicus, taking care to avoid skin compression and after patients exhaled. All patients underwent a measurement of HDL levels. Other variables collected were age, PSA value, BMI, and Gleason score according to biopsy results. Patients were divided in two groups according to PCa diagnosis: Group A included patients with a positive biopsy and Group B those without malignant disease. All patients were informed regarding the aims and design of the study and were included after signing an informed consent. The institutional review board of the hospital approved study protocol before initiation and all patients were managed according to the principles of Helsinki Declaration. Statistical analysis Continuous variables are described as means ± SDs or medians depending on whether there was normal distri- bution or not, while categorical variables are described with proportions. We performed independent sample t- test for comparing continuous variables when assump- tion for normality was met, as indicated by Shapiro- Wilk test. If normality assumption was not met, comparison of continuous variables was performed using Mann- Whitney U test. Comparison of categorical variables was performed either with chi-square or Fisher’s exact test, depending on the number of observations in each cell of the variable. Binary logistic regression was performed to detect the effect of age, MetS and each one of the five components (central obesity, triglycerides > 150 mg/dl, HDL < 40 mg/dl, diabetes mellitus, and hypertension) on occurrence of prostate cancer. Linearity of the continuous variables used in the regression model regarding the logit of dependent variable was assessed with the Box- Tidwell procedure. A Bonferroni correction was applied using all terms in the model created. Based on this test, all contin- uous independent variables were linearly associated to the logit of the dependent variable. No significant outliers were detected during performance of the binomial regres- sion model. All analyses were performed using IBM SPSS Statistics v. 23 (IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.). RESULTS Prospective data collection was performed for 378 patients within the two-year period of the study (2018- 2019). Mean patient age, body mass index and waist cir- cumference did not differ significantly between the two groups (Table 2). Mean PSA value was 8.7 ng/dl in the PCa group and 7.1 ng/dl in the non PCa group, respec- tively (p < 0.001). Besides PSA value, both triglycerides (166 vs 146 mg/dl, p < 0.001) and HDL cholesterol (46 vs 44.4 mg/dl, p < 0.001) were higher in patients diag- nosed with prostate cancer (Table 2). Table 2. Baseline patient characteristics. Patients with PCa Patients without PCa p-value No patients, n (%) 197 (52.1) 181 (47.9) Age (years) 64.6 (8) 65 (7.2) 0.620 PSA (ng/ml) 8.7 (3.2) 7.1 (2.4) < 0.001 BMI (kg/m2) 28.6 (3) 27.9 (2.7) 0.178 Waist circumference (cm) 108 (8.6) 104.3 (7.7) 0.233 Triglycerides (mg/dl) 166 (50) 146 (39) < 0.001 HDL (mg/dl) 46 (8.3) 44.4 (6.7) < 0.001 PCa = Prostate cancer. * Numbers are presented as means (± SD). Table 1. American Heart Association criteria for diagnosis of Metabolic Syndrome. 1. Fasting glucose ≥ 100 mg/dL (or drug therapy for hyperglycemia) 2. Blood pressure ≥ 130/85 mmHg (or drug therapy for hypertension) 3. Triglycerides ≥ 150 mg/dL (or drug therapy for hypertriglyceridemia) 4. HDL cholesterol < 40 mg/dL (or drug therapy for reduced HDL) 5. Waist circumference ≥ 102 cm 293Archivio Italiano di Urologia e Andrologia 2021; 93, 3 Association between metabolic syndrome and prostate cancer diagnosis MetS was diagnosed in 108 patients (54.8%) with and 80 patients (44.2%) without PCa (p = 0.039). Patients with PCa more frequently suffered from abnormal levels of triglycerides, compared to healthy patients (59.9% vs 42.5% respectively, p = 0.001), as shown in Table 3. MetS was diagnosed in 42 patients (65.6%) with higher Gleason score PCa (GS ≥ 4+3) and in 66 patients (49.6%) with lower Gleason score PCa (≤ 3+4), p = 0.035. (Table 4). Individual components of metabolic syndrome did not differ significantly in patients with higher Gleason score PCa, compared to those with lower Gleason score PCa disease (Table 4). Age (OR 1.061, 95% C.I.: 1.016- 1.107, p = 0.007) and presence of metabolic syndrome (OR 5.949, 95% C.I.: 1.503-23.543, p = 0.011) seem to increase the risk for higher Gleason score PCa occur- rence, while hypertriglyceridemia (OR 0.309, 95% C.I.:0.104-0.916, p = 0.034) and low HDL (OR 0.260, 95% C.I.: 0.102-0.659, p = 0.005) seem to be protective factors according to logistic regression analysis (Table 5). Further analysis was implemented regarding the associa- tions between age and MetS and its components with PCa (Supplementary Table 1). Triglycerides > 150 mg/dl were associated with PCa (p = 0.012). Additional analysis was conducted regarding the associations between age and MetS and its components and highest Gleason score PCa (GS ≥ 4+4) (Supplementary Table 2). Age was signifi- cantly associated with high Gleason score PCa in the study population (p = 0.007). DISCUSSION MetS is described as a multi-level risk factor combining insulin resistance, abnormal adipose fat deposition, hypertension, increased levels of triglycerides and low levels of HDL cholesterol. As a risk factor, it is associated with a high risk of atherosclerotic cardiovascular disease and type 2 diabetes (1, 2). Additionally, MetS is associated with some common forms of cancer, with existing data suggesting that it can negatively affect cancer mortality (5). Although the only established risk factors for PCa devel- opment include age, ethnic origin, and family history there are data suggesting that environmental factors, such as eating habits or physical activity, may also play a role in the etiology of the disease. The adoption of poor eating habits combined with reduced physical activity may be an explanation for the rising rates of PCa in Asian popu- lations living in the United States, compared to lower inci- dence of PCa in Asia (12). Nevertheless, there is no cur- Table 3. Comparison of metabolic syndrome components between patients with and without prostate cancer (PCa). Patients with PCa Patients without PCa p-value * n (%) n (%) MetS 108 (54.8) 80 (44.2) 0.039 Central obesity 139 (70.6) 110 (60.8) 0.061 High triglycerides 118 (59.9) 77 (42.5) 0.001 Low HDL 45 (22.8) 45 (24.9) 0.645 Diabetes mellitus 81 (41.1) 75 (41.4) 0.950 Hypertension 125 (63.5) 111 (61.3) 0.670 MetS = Metabolic Syndrome. * Comparisons between groups were performed using Chi-square test. Table 4. Chi-square for metabolic syndrome components on higher Gleason score PCa vs lower Gleason score prostate cancer (PCa). Patients with higher Patients with lower p-value Gleason score PCa Gleason score PCa (GS ≥ 4+3) n (%) (GS ≤ 3+4) n (%) MetS 42 (65.6) 66 (49.6) 0.035 Central obesity 50 (78.1) 88 (66.2) 0.086 High triglycerides 40 (62.5) 78 (58.6) 0.605 Low HDL 10 (15.6) 35 (26.3) 0.096 Diabetes mellitus 23 (35.9) 58 (43.6) 0.305 Hypertension 43 (67.2) 82 (61.7) 0.450 MetS = Metabolic Syndrome; PCa = Prostate cancer; GS = Gleason score. * Comparisons between groups were performed using Chi-square test. Table 5. Variables associated with higher Gleason score prostate cancer (PCa) (GS ≥ 4+3). p value Odds ratio (OR) 95% C.I. Lower Higher Age 0.007 1.061 1.016 1.107 Metabolic syndrome 0.011 5.949 1.503 23.543 Central obesity 0.912 1.059 0.381 2.943 Triglycerides > 150 mg/dl 0.034 0.309 0.104 0.916 HDL < 40 mg/dl 0.005 0.260 0.102 0.659 Diabetes mellitus 0.102 0.531 0.249 1.134 Hypertension 0.685 0.844 0.373 1.913 Supplementary Table 1. Variables associated with PCa. p value Odds ratio (OR) 95% C.I. Lower Higher Age 0.579 0.992 0.965 1.020 Metabolic syndrome 0.552 0.780 0.343 1.772 Central obesity 0.551 1.195 0.666 2.144 Triglycerides > 150 mg/dl 0.012 2.310 1.201 4.446 HDL < 40 mg/dl 0.935 1.022 0.611 1.708 Diabetes mellitus 0.570 0.870 0.539 1.405 HTN 0.957 1.013 0.631 1.627 Supplementary Table 2. Variables associated with high grade PCa (GS ≥ 4+4). p value Odds ratio (OR) 95% C.I. Lower Higher Age 0.007 1.090 1.024 1.161 Metabolic syndrome 0.348 2.464 0.375 16.179 Central obesity 0.459 1.738 0.402 7.512 Triglycerides > 150 mg/dl 0.294 0.450 0.102 1.997 HDL < 40 mg/dl 0.147 0.371 0.097 1.416 Diabetes mellitus 0.663 0.789 0.271 2.295 Hypertension 0.841 0.887 0.275 2.863 Archivio Italiano di Urologia e Andrologia 2021; 93, 3 C. Fragkoulis, I. Glykas, L. Tzelves, K. Stasinopoulos, L. Lazarou, A. Kaoukis, A. Dellis, G. Stathouros, G. Papadopoulos, K. Ntoumas 294 rent evidence suggesting that dietary preventing measures may reduce the risk of PCa development, since the out- comes of the selenium and vitamin E cancer prevention trial (SELECT) failed to show significant results (13). Existing evidence about the association of PCa with MetS is conflicting (14). A series of meta-analyses have demon- strated contradictory results regarding the presence of a significant association between MetS and PCa incidence. Esposito et al. in their meta-analysis, reported that meta- bolic syndrome was associated with a 12% increase in prostate cancer risk (10). In this metanalysis the associa- tion between MetS and PCa was significant in the European studies, but not in the U.S. and Asian studies included. Risk estimations of PCa for higher values of body mass index, dysglycemia or dyslipidemia were not significant, while on the contrary the remaining two com- ponents of MetS, namely hypertension and waist circum- ference > 102 cm, were associated with a significantly greater risk of prostate cancer. Therefore, MetS is weakly associated with the risk of PCa with different results reported from several geographical locations (10). Furthermore, in a Canadian population-based, case-con- trol study by Blanc-Lapierre et al., the association between MetS and PCa was also investigated (11). Nearly 2000 men (1937) with incidental prostate cancer, aged ≤ 75 years and diagnosed between 2005 and 2009 were evalu- ated and their detailed lifestyle, medical history, and anthropometric measures, were collected. A history of MetS (≥ 3 components) was associated with a reduced risk of prostate cancer, suggesting a synergistic interac- tion of the components. Findings from this study were consistent with a reverse association between MetS and prostate cancer risk (11). Moreover, the meta-analysis performed by Xiang et al. failed to detect any association between the two entities, a result probably originating both from the heterogeneity of included studies and the fact that the individual components of the metabolic syn- drome might exert antagonistic actions between them. However, it was demonstrated that the metabolic syn- drome is related to prostate cancer of higher Gleason score or advanced clinical stage or even increased prostate cancer-specific mortality (15). On the other hand, a non-systematic review by De Nunzio et al., suggests an association between MetS and its medi- ators which affect the prostate microenvironment with the initiation and clinical progression of benign prostate hyperplasia and PCa, although these molecular pathways remain incompletely described (16). More recently, in a study by Bhindi et al, including 2.235 patients with prostate cancer, of whom 22.1% had metabolic syn- drome, it was demonstrated that although no individual component of metabolic syndrome was independently associated with cancer, there was an increasing associa- tion between the number of metabolic abnormalities and both the diagnosis and grade of cancer (17). As far as it concerns the pathophysiology of MetS, central obesity is considered to be the initial step for the devel- opment and the progression of the disease. As a result of dysfunctional adipose fat deposition, proinflammatory cytokines and other molecules are released leading to insulin resistance (18). These proinflammatory sub- stances, triggered by central obesity and resulting into insulin resistance, include resistin, leptin, interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-a), fibrinogen, plasminogen, and c-reactive protein (CRP) (2). A potential molecular mechanism explaining the correla- tion of MetS and PCa is based on insulin resistance. Insulin-growth-factor 1 (IGF-1) levels are increased in patients presenting with insulin resistance. IGF-1 may stimulate growth of both androgen sensitive and andro- gen independent human PCa cell lines in vitro (19). Moreover, a polymorphism within the leptin genetic sequence leading to increased leptin production, was associated with higher risk of advanced PCa disease (19). On a population level, metformin users were found to be at a decreased risk of PCa diagnosis compared to non- users (20). On the other hand, in 540 diabetic partici- pants of the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) study, metformin use was not signifi- cantly associated with PCa and therefore not advised as a preventive measure (21). A meta-analysis of 14 large prospective studies did not show any association between blood total cholesterol, high-density lipoprotein (HDL) cho- lesterol, low-density lipoprotein (LDL) cholesterol levels and the risk of either overall PCa or high-grade PCa (22). Results from the REDUCE study also did not show a pre- ventive effect of statins on PCa risk (21). Within the REDUCE study, obesity was associated with lower risk of low-grade PCa in multivariable analyses, but increased risk of high-grade PCa (23). In addition, obesity is characterized by low serum levels of adiponectin, which is believed to have anti-angio- genetic and possible antitumor properties, but its role has not been fully understood yet (24). The findings of our study agree with those of similar stud- ies, as that of De Nunzio, which also implies an associa- tion between metabolic syndrome and high-grade prostate cancer (25). More specifically, among Italian men with elevated PSA level or abnormal digital rectal examination, MetS was present in 44% of all patients. Although MetS was not associated with more frequent diagnosis of PCa overall, it was associated with an increased risk of Gleason score 7 or higher disease (25). Although the exact molecular pathways remain incom- pletely described, a possible association with PCa may be present, triggered by proinflammatory cytokines, chronic prostate inflammation, and hormones such as leptin and adiponectin. Western culture and way of life is often characterized by poor dietary habits and less physical exercise and is commonly adopted in Greece. The present study presents data suggesting that Greek patients pre- senting with elevated levels of PSA or abnormal digital rectal examination have an increased risk of PCa detec- tion after a prostate biopsy when they fulfill the criteria for MetS diagnosis. Moreover, these patients have a trend to present with a worse Gleason score when compared to patients not suffering from MetS. A potential limitation is that patients were recruited only at one large, Metropolitan center with no patients from remote areas included. Another possible limitation is the relatively small sample size of 378 patients. To our knowledge this is the first Greek study correlating MetS with PCa cancer diagnosis and GS in patients under- going transrectal ultrasound guided prostate biopsy. 295Archivio Italiano di Urologia e Andrologia 2021; 93, 3 Association between metabolic syndrome and prostate cancer diagnosis CONCLUSIONS MetS is a complex disorder with multiple organ targets and severe effects on public health. Thus, it is quite important for urologists to be familiar with MetS, to rec- ognize it and consult their patients accordingly as simple alterations in lifestyle habits may prevent or delay the occurrence high Gleason score PCa development. It is mandatory to further investigate the correlation of MetS with PCa with studies involving higher numbers of patients. REFERENCES 1. Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Nech. 2009; 2:231-237. 2. Grundy SM. Metabolic syndrome: a multiplex cardiovascular risk factor. J Clin Endocrinol Metab. 2007; 92:399-404. 3. Ford ES, Giles WH, Mokdad AH. Increasing prevalence of the metabolic syndrome among U.S. adults. Diabetes Care. 2004; 27:2444-2449. 4. Parazzini F, Artibani W, Carrieri G, et al. Effect of body mass and physical activity at younger age on the risk of prostatic enlargement and erectile dysfunction: Results from the 2018 #Controllati survey. Arch Ital Urol Androl. 2020; 91:245-250. 5. Zhou JR, Blackburn GL, Walker WA. Symposium introduction: metabolic syndrome and the onset of cancer. Am J Clin Nutr. 2007; 86:s817-s819. 6. Renehan AG, Tyson M, Egger M, et al. Body-mass index and inci- dence of cancer: a systematic review and meta-analysis of prospec- tive observational studies. Lancet. 2008; 371:569-578. 7. Nicolucci A. Epidemiological aspects of neoplasms in diabetes. Acta Diabetol. 2010; 47:87-95. 8. Jafri H, Alsheikh-Ali AA, Karas RH. Baseline and on-treatment high-density lipoprotein cholesterol and the risk of cancer in ran- domized controlled trials of lipid altering therapy. J Am Coll Cardiol. 2010; 55:2846-2854. 9. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015; 1; 136:E359-86. 10. Esposito K, Chiodini P, Capuano A, et al. Effect of metabolic syn- drome and its components on prostate cancer risk: meta-analysis. J Endocrinol Invest. 2013; 36:132-139. 11. Blanc-Lapierre A, Spence A, Karakiewicz PI, et al. Metabolic syndrome and prostate cancer risk in a population-based case-con- trol study in Montreal, Canada. BMC Public Health. 2015; 18; 15:913. 12. Hsing AW, Sakoda LC, Chua Jr S. Obesity, metabolic syndrome and prostate cancer. Am J Clin Nutr. 2007; 86:843-857. 13. Lippman SM, Klein EA, Goodman PJ, et al. Effect of selenium and vitamin E on risk of prostate cancer and other cancers: the Selenium and Vitamin E Cancer Prevention Trial (SELECT). JAMA. 2009; 301:39-51. 14. Fragkoulis C, Glykas I, Gkialas I, et al. The role of nutrition in the prevention of prostatic adenocarcinoma. J BUON. 2017; 22:1085-1086. 15. Xiang YZ, Xiong H, Cui ZL, et al. The association between meta- bolic syndrome and the risk of prostate cancer, high-grade prostate cancer, advanced prostate cancer, prostate cancer-specific mortality and biochemical recurrence. J Exp Clin Cancer Res. 2013; 13; 32:9. 16. De Nunzio C, Aronson W, Freedland SJ, et al. The correlation between metabolic syndrome and prostatic diseases. Eur Urol 2012; 61:560-570. 17. Bhindi B, Locke J, Alibhai SM, et al. Dissecting the association between metabolic syndrome and prostate cancer risk: analysis of a large clinical cohort. Eur Urol. 2015; 67:64-70. 18. Gustafson B, Hammarstedt A, Andersson CX, et al. Inflamed adi- pose tissue: a culprit underlying the metabolic syndrome and athero- sclerosis. Arterioscler Thromb Vasc Biol. 2007; 27:2276-2283. 19. Buschemeyer III WC, Freedland SJ. Obesity and prostate cancer: epidemiology and clinical implications. Eur Urol. 2007; 52:331-343. 20. Preston MA, Riis AH, Ehrenstein V, et al. Metformin use and prostate cancer risk. Eur Urol. 2014; 66:1012-20. 21. Freedland SJ, Hamilton RJ, Gerber L, et al. Statin use and risk of prostate cancer and high-grade prostate cancer: results from the REDUCE study. Prostate Cancer Prostatic Dis. 2013; 16:254-9. 22. YuPeng L, YuXue Z, PengFei L, et al. Cholesterol levels in blood and the risk of prostate cancer: a meta-analysis of 14 prospective studies. Cancer Epidemiol Biomarkers Prev. 2015; 24:1086-93. 23. Vidal AC, Howard LE, Moreira DM, et al. Obesity increases the risk for high-grade prostate cancer: results from the REDUCE study. Cancer Epidemiol Biomarkers Prev. 2014; 23:2936-42. 24. Brakenhielm E, Veitonmaki N, Cao R, et al. Adiponectin induced antiangiogenesis and antitumor activity involve caspase-mediated endothelial cell apoptosis. Proc Natl Acad Sci USA 2004; 101:2476- 2481. 25. De Nunzio C, Freedland SJ, Miano R, et al. Metabolic syndrome is associated with high grade gleason score when prostate cancer is diagnosed on biopsy. Prostate 2011; 71:1492-1498. Correspondence Charalampos Fragkoulis, MD harisfrag@yahoo.gr Georgios Stathouros, MD gstathouros@yahoo.gr Georgios Papadopoulos, MD gipapadopoulos@yahoo.gr Konstantinos Ntoumas, MD ntoumask@yahoo.com Ioannis Glykas, MD (Corresponding Author) giannis.glykas@gmail.com Department of Urology, General Hospital of Athens G. Gennimatas Leof. Mesogeion 154 Athens (Greece) Lazaros Tzelves, MD lazarostzelves@gmail.com Lazaros Lazarou, MD lazarou_laz@hotmail.com 2nd Department of Urology, National and Kapodistrian University of Athens, School of Medicine, Sismanoglio Hospital, Athens (Greece) Konstantinos Stasinopoulos, MD konstasinopoulos@gmail.com Department of Urology, General Hospital of Lakonia, Sparta (Greece) Andreas Kaoukis, MD andreaskaoukis@yahoo.gr Department of Cardiology, General Hospital of Athens ‘’G. Gennimatas’’, Athens (Greece) Athanasios Dellis, MD aedellis@gmail.com 2nd Department of Surgery, Aretaieion Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens (Greece)