Literature DB >> 23406686

The association between metabolic syndrome and the risk of prostate cancer, high-grade prostate cancer, advanced prostate cancer, prostate cancer-specific mortality and biochemical recurrence.

Yu-zhu Xiang1, Hui Xiong, Zi-lian Cui, Shao-bo Jiang, Qing-hua Xia, Yong Zhao, Guan-bin Li, Xun-bo Jin.   

Abstract

BACKGROUND: Although a previous meta-analysis reported no association between metabolic syndrome (MetS) and prostate cancer risk, a number of studies suggest that MetS may be associated with the aggressiveness and progression of prostate cancer. However, these results have been inconsistent. This systematic review and meta-analysis investigated the nature of this association.
METHODS: We systematically searched MEDLINE, EMBASE and bibliographies of retrieved studies up to January 2013 using the keywords "metabolic syndrome" and "prostate cancer". We assessed relative risks (RRs) of the prostate cancer, several parameters of prostate cancer aggressiveness and progression associated with MetS using 95% confidence intervals (95% CIs).
RESULTS: The literature search produced 547 hits from which 19 papers were extracted for the meta-analysis. In cancer-free population with and without MetS, the combined adjusted RR (95% CI) of prostate cancer risk and prostate cancer-specific mortality in longitudinal cohort studies is 0.96 (0.85 ~ 1.09) and 1.12 (1.02 ~ 1.23) respectively. In the prostate cancer patients with and without MetS, the combined unadjusted OR (95% CI) of high grade Gleason prostate cancer is 1.44 (1.20 ~ 1.72), the OR of advanced prostate cancer is 1.37 (1.12 ~ 1.68) and the OR of biochemical recurrence is 2.06 (1.43 ~ 2.96).
CONCLUSIONS: The overall analyses revealed no association between MetS and prostate cancer risk, although men with MetS appear more likely to have high-grade prostate cancer and more advanced disease, were at greater risk of progression after radical prostatectomy and were more likely to suffer prostate cancer-specific death. Further primary studies with adjustment for appropriate confounders and larger, prospective, multicenter investigations are required.

Entities:  

Mesh:

Year:  2013        PMID: 23406686      PMCID: PMC3598969          DOI: 10.1186/1756-9966-32-9

Source DB:  PubMed          Journal:  J Exp Clin Cancer Res        ISSN: 0392-9078


Background

In men, prostate cancer (PCa) is the most frequently diagnosed malignancy in industrialized countries [1] and it is the second most commonly diagnosed cancer and the sixth leading cause of cancer death worldwide [2]. There is a clear need for a better understanding of the risk factors related to PCa development and progression. Age, race and family history are the only established prostate cancer risk factors and these factors are all non-modifiable. Recently, modifiable lifestyle factors such as physical activity and diet have been investigated. Because a higher incidence of PCa was associated with a higher prevalence of “western” lifestyle, it has been suggested that these lifestyle factors play a significant role in the pathogenesis of PCa [3]. Metabolic syndrome (MetS) is a cluster of cardiovascular risk factors that includes hypertension, diabetes mellitus, obesity, hypertriglyceridemia, and low high-density lipoprotein cholesterol, with insulin resistance as the underlying hallmark feature [4]. The prevalence of MetS has been increasing worldwide and has become a major public health problem in many western countries. For example, 35%-41% of adults in the USA are reported to exhibit MetS [5]. Recently, increasing evidences suggests that MetS may be involved in the development and progression of certain types of cancer as an independent etiologic factor including breast cancer [6], endometrial cancer [7], colorectal cancer [8], pancreatic cancer [9] and prostate cancer [10]. MetS was firstly observed as a composite factor associated with prostate cancer risk in 2004 [11], and more studies have since reported the association between MetS and prostate cancer. However, the studies investigating the association between MetS and prostate cancer risk have reported inconsistent findings [12-21]. It is crucial to review and evaluate the magnitude to which MetS affects the development and progression of PCa, as proper management of this modifiable lifestyle factor may help improve PCa outcomes. A recently performed meta-analysis study summarized the association between MetS and the incidence of some common cancer types, including prostate cancer. The results, based on 14 databases, revealed that MetS was not associated with prostate cancer risk [22]. However, a new investigation on MetS and prostate cancer risk was published recently [19], and much increasing evidence in the latest investigations suggests that MetS may be associated with the aggressiveness and progression of PCa; prostate cancer patients with MetS may suffer more aggressive disease and adverse clinical outcomes [19,23-27]. However, inverse results [28] or no significant associations [14,20,29,30] have been reported in other studies. Therefore, to thoroughly investigate the nature of this association, we focused on longitudinal cohort studies and conducted a new meta-analysis to confirm the association between MetS and prostate cancer risk by searching the latest literature. Subsequently, we performed another meta-analysis to quantitatively summarize several parameters of PCa aggressiveness and progression, including Gleason score, clinical stage, biochemical recurrence and prostate cancer-specific mortality associated with MetS.

Methods

Search strategy

We systematically searched MEDLINE, EMBASE through January 2013 for human studies on the association between MetS and PCa with the following medical subject heading terms and/or text words: “metabolic syndrome”, “insulin resistance syndrome”, or “syndrome X”, combined with “prostate cancer”, “prostatic cancer”, “prostate neoplasm”, or “prostatic neoplasm”. We also manually searched relevant journals, bibliographies, and reviews for additional articles. The search had no language restriction.

Inclusion criteria

The eligibility of each study was assessed independently by two investigators (YX and HX). We included only cohort studies of MetS and prostate cancer risk or prostate cancer-specific mortality and clinical studies of MetS and Gleason score or clinical stage at diagnosis or biochemical recurrence after treatment. We included studies that reported standardized forms of relative risk, risk ratio, hazard ratio or odds ratio with estimates of confidence intervals (CIs) or with sufficient data to estimate CIs. We used relative risks (RRs) to represent various effect estimates in a cohort study in this meta-analysis.

Exclusion criteria

We excluded reviews, editorials, meta-analysis and animal studies. Among the 23 studies that underwent full-text reviews, we excluded a study on MetS and prostate cancer risk of re-biopsy [31], a study that did not use a standard definition of MetS [32,33] and one case-control study on MetS and prostate cancer risk [21]. For studies previously published on the same database [34,35], we included only the most recent findings [19,20]. All of the studies on which we focused reported RRs with 95% CIs or sufficient data to estimate them.

Data extraction

The data extracted included publication data (the first author’s last name, year of publication, and country of the population studied), study design, population resources, number of cases, risk estimates with their corresponding CIs, and variables controlled for by matching or in the most adjusted model. Abstractions of the data elements were conducted separately by two authors; discordant results were resolved by consensus.

Statistical analysis

Firstly, we updated the data and attempted to analyze the association of MetS with the prostate cancer risk in longitudinal cohort studies only. Subsequently, we assessed the association between MetS and prostate cancer-specific mortaligy in cohort studies and between MetS and high grade Gleason PCa and/or advanced PCa or biochemical recurrence in clinical studies. We pooled all of the RRs for MetS and assessed the heterogeneity between the studies by Q and I2 statistics, which are distributed as x2 statistics [36]. A value of P < 0.10 was used to indicate lack of homogeneity (heterogeneity) among effects. We used a fixed-effects model if I2 value significance was <0.1; otherwise, we used a random-effect model. Sensitivity analysis was conducted by omitting one study at a time, generating the pooled estimates and comparing with the original estimates. Funnel plots and both Begg’s and Egger’s tests were used to evaluate publication bias. All analyses were performed using STATA version 9.0 statistical software (Stata, College Station, Texas, USA). All statistical comparisons were 2-sided, and a p-value < 0.05 was considered statistically significant).

Results

Study characteristics

Nineteen studies met the search inclusion and exclusion criteria. The characteristics of included studies are presented in Tables 1 and 2.
Table 1

Characteristics of cohort studies of metabolic syndrome and prostate cancer risk

Author yr (ref. no.)CountryPopulationMean age, yrMean FU time, yrTime periodCohort sizeDefinition of MetSNo. of casesRRs95% CIControlled variables
Laukkanen 2004 [11]
Finland
Kuopio communities
52.6
15
1984-2001
1,880
WHO
56
RR 1.90
1.1-3.5
Age
Tande 2006 [12]
United States
ARIC* (49% white, 51% African American)
45-64
12.1
1987-2000
6,429
NCEP-ATP-III
385
RR 0.77
0.60-0.98
Age, race
Russo 2008 [13]
Italy
A pharmacologically based diagnosis
40
2.7
1999-2005
NA
A pharmacologically based diagnosis
94
RR 0.93
0.75-1.14
Age
Martin 2009 [14]
Norway
HUNT2
48 ± 16.4
9.3
1996-2005
29,364
NCEP-ATP-III
687
RR 0.91
0.77-1.09
Age+
Inoue 2009 [15]
Japan
Japan PHC population
40-69
10.2
1993-2004
9,548
IDF
119
HR 0.76
0.47-1.22
Age+
Grundmark 2010 [16]
Sweden
ULSAM
50
30.3
1970-2003
2,183
NCEP-ATP-III
226
RR 1.29
0.89-1.88
Age
2,287
IDF
234
RR 1.18
0.81-1.71
Wallner 2010 [17]
United States
Olmsted County
40-79
15
1990-NA
2,445
WHO
206
HR 0.65
0.37-1.10
Age
Osaki 2011 [18]
Japan
The population-based cancer registry
60.5 ± 10.8
9.3
1992-2007
8,239
NCEP-ATP-III
152
HR 1.37
0.91-2.06
Age
8,239
IDF
152
HR 1.18
0.74-1.90
Häggström 2012 [19]Norway
Me-Can4412NA289,866Upper quartile levels ATP-III criteria6,922RR 0.960.92-1.00Age+
Sweden
Austria

MetS = metabolic syndrome; PCa = prostate cancer; RRs = Relative risks; CI = confidence interval; Age + =At least age; WHO = World Health Organization; NCEP-ATP-III = National Cholesterol Education Program Adult Treatment Panel III; IDF = International Diabetes Federation; HUNT 2 = Nord-Trondelang Health Study; ARIC = Atherosclerosis Risk in Communities; OR = odds ratio; *We use White-American data.

Table 2

Characteristics of studies of metabolic syndrome and parameters of prostate cancer

Author yr (ref. no.)CountryStudy designPopulationMean age,yrTime periodDefinition Vof MetSNo. of casesOutcomesRRs95% CI
B.K 2007 [29]
Korea
Cross-section study
Patients who underwent radical retropubic prostatectomy
64.8 ± 6.2
2004-2006
NCEP-ATP-III
261
Gleason score ≥7(4 + 3)
0.972
0.637-1.482
Clinical stage ≥ T3
0.991
0.532-1.846
Beebe-Dimmer 2009 [20]
United States
Case-control study
GECAP
62.3
1999-2004
NCEP-ATP-III
637
Gleason score ≥7(4 + 3)
1.2
0.64-2.27
Clinical stage ≥ T3
1.17
0.55-2.51
Castillejos-Molina 2011 [23]
Mexico
Case-control study
Patients with PC who underwent surgical treatment
64.8 ± 6.97
1990-2007
WHO
210
Gleason score >7
3.346
1.144-9.791
Clinical stage ≥ T3
1.628
0.915-2.896
Kheterpal 2012 [24]
United States
Cross-section study
Patients who underwent robot assisted radical prostatectomy
60.7 ± 6.9
2005-2008
IDF
2756
Gleason score ≥7(4 + 3)
1.328
0.978-1.802
Clinical stage ≥ T3
1.416
1.109-1.808
De Nunzio 2011 [25]
Italy
Cross-section study
Patients who underwent prostate biopsy for PSA > 4 ng/ml or abnormal DRE
69
2009-2011
NCEP-ATP-III
83
Gleason score ≥7
3.82
1.33-10.9
Clinical stage ≥ T3
NA
NA
Jeon 2012 [28]
Korea
Cross-section study
Patients who underwent prostate biopsy for PSA > 4 ng/ml or abnormal DRE
68.86 ± 8.95
2003-2011
NCEP-ATP-III
90
Gleason score ≥7(4 + 3)
0.101
0.022-0.473
Clinical stage ≥ T3
NA
NA
Morote 2012 [26]
Spain
Cross-section study
Patients who underwent prostate biopsy for PSA > 4 ng/ml or abnormal DRE
68(46-79)
2006-2010
NCEP-ATP-III
848
Gleason score >7
1.75
1.260-2.414
Clinical stage ≥ T3
NA
NA
Castillejos-Molina 2011 [23]
Mexico
Case-control study
Patients with PC who underwent surgical treatment
64.8 ± 6.97
1990-2007
WHO
210
Biochemical recurrence
2.73
1.65-4.50
Post 2011 [27]
United States
Case-control study
Patients who underwent radical prostatectomy
60.9
1999- 2004
NCEP-ATP-III
383
Biochemical recurrence
1.5
0.90-2.6
Jaggers 2009 [30]
United States
Cohort study
Aerobics Center Longitudinal Study
20-88
1977-2003
NCEP-ATP-III
185
Mortality
1.32
0.63-2.77
Martin 2009 [14]
Norway
Cohort study
HUNT2
48 ± 16.4
1996-2005
NCEP-ATP-III
107
Mortality
0.81
0.52-1.25
Häggström 2012 [19]Norway Sweden AustriaCohort studyMe-Can44NAUpper quartile Levels ATP-III criteria961Mortality1.131.03-1.25

PCa = prostate cancer; RRs = Relative risks; CI = confidence interval; WHO = World Health Organization; NCEP-ATP-III = National Cholesterol Education Program Adult Treatment Panel III; IDF = International Diabetes Federation; HUNT 2 = Nord-Trondelang Health Study; NA = Not available; DRE = Digital rectal examination.

Characteristics of cohort studies of metabolic syndrome and prostate cancer risk MetS = metabolic syndrome; PCa = prostate cancer; RRs = Relative risks; CI = confidence interval; Age + =At least age; WHO = World Health Organization; NCEP-ATP-III = National Cholesterol Education Program Adult Treatment Panel III; IDF = International Diabetes Federation; HUNT 2 = Nord-Trondelang Health Study; ARIC = Atherosclerosis Risk in Communities; OR = odds ratio; *We use White-American data. Characteristics of studies of metabolic syndrome and parameters of prostate cancer PCa = prostate cancer; RRs = Relative risks; CI = confidence interval; WHO = World Health Organization; NCEP-ATP-III = National Cholesterol Education Program Adult Treatment Panel III; IDF = International Diabetes Federation; HUNT 2 = Nord-Trondelang Health Study; NA = Not available; DRE = Digital rectal examination. Detailed search steps are described in Figure 1. Briefly, from the initial literature search we identified 547 abstracts. Twenty-three articles were considered of interest and full text of each article was retrieved for detailed evaluation. Eleven studies investigated the association between MetS and prostate cancer [11-21]. Nine of them were longitudinal cohort studies that reported the RRs of PCa in cancer-free population with and without MetS [7-15]. Seven studies evaluated MetS and pathological and clinical stages of PCa, of these studies, 7/7 investigate Gleason score [20,23-26,28,29] and 4/7 investigated clinical stage [20,23,24,29]. Two case-control studies explored biochemical recurrence after primary treatment [23,27], and three longitudinal cohort studies focused on prostate cancer-specific mortality [14,19,30].
Figure 1

Selection of studies for meta-analysis.

Selection of studies for meta-analysis.

Main findings

Prostate cancer risk

Result from a meta-analysis based on nine longitudinal cohort studies revealed that there was no association between MetS and prostate cancer risk (RR = 0.96, 95% CI 0.85-1.09 n = 9 studies) (Figure 2).
Figure 2

RR of prostate cancer risk for MetS presence.

RR of prostate cancer risk for MetS presence.

Prostate cancer aggressiveness

High grade Gleason score

The definition of high grade Gleason score is ≥ 7 or > 7. A trend for a 36% increased risk of a high Gleason score in patients with MetS (OR = 1.36, 95% CI 0.90-2.06 n = 7 studies) was identified based on a meta-analysis of seven total relative databases (Figure 3).
Figure 3

RR of high grade Gleason prostate cancer risk for MetS presence.

RR of high grade Gleason prostate cancer risk for MetS presence.

Advanced clinical stage

Advanced clinical stage was defined as a clinical stage ≥ T3. Four databases were included in the analysis of the association of MetS with advanced clinical stage. The analysis revealed that MetS was significantly associated with a 37% increased risk of advanced clinical stage (OR = 1.37, 95% CI: 1.12 ~ 1.68; n = 4 studies) (Figure 4).
Figure 4

RR of advanced clinical stage for MetS presence.

RR of advanced clinical stage for MetS presence.

Prostate cancer progression

Biochemical recurrence

Only two databases [23,27] focused on the association of MetS which biochemical recurrence. The Individual study results and the overall summary results are presented in Figure 5. The result indicates that MetS was significantly associated with 2-folds of increased risk of biochemical recurrence (OR = 2.06, 95% CI: 1.43-2.96, n = 2 studies).
Figure 5

RR of biochemical recurrence for MetS presence.

RR of biochemical recurrence for MetS presence.

Prostate cancer-specific mortality

Three cohort studies [14,19,30] investigated how MetS affected prostate cancer-specific mortality. The meta-analysis revealed that MetS was significantly associated with a higher risk of the prostate cancer-specific death (RR = 1.12, 95% CI: 1.02 ~ 1.23; n = 3 studies) (Figure 6).
Figure 6

RR of prostate cancer-specific mortality for MetS presence.

RR of prostate cancer-specific mortality for MetS presence.

Sensitivity analysis

We conducted sensitivity analysis by omitting one study at a time, generating the pooled estimates and comparing the pooled estimates with the original estimates. Omitting any one of nine studies concerning MetS and prostate cancer risk or omitting any one of four studies concerning MetS and advanced clinical stage produced no dramatic influence on the original pooled RRs. Omitting Jeon 2012 database [28] in the 7 studies concerning MetS and Gleason score produced a significant OR = 1.44 (95% CI: 1.20 ~ 1.72), whereas none of the remaining severn studies exhibited a significant influence on the original estimates. For biochemical recurrence and prostate cancer-specific mortality, there were too few studies to do a sensitivity analysis.

Publication bias

Visual inspection of the Begg funnel plot for both PCR and Gleason score did not reveal the asymmetry typically associated with publication bias (Figure 7). Evidence of publication bias was also not seen with the Egger or Begg tests (Egger P = 0.27 and 0.64 for prostate cancer risk and Gleason score respectively).
Figure 7

Funnel plot with pseudo 95% confidence limits.

Funnel plot with pseudo 95% confidence limits.

Discussion

In 2007, Hsing et al. summarized five studies on MetS and prostate cancer risk and concluded that the epidemiologic evidence was insufficient to suggest a link between MetS and PCa [37]. In 2012, Esposito et al. performed a systematical review and meta-analysis on the association of MetS and cancer risk including prostate cancer. The authors also concluded that MetS was not associated with prostate cancer risk too [22]. In the present study, we updated the data and used the current evidence to analyze whether MetS is associated with prostate cancer risk. We observed the same result as previous meta-analysis; no association could be detected between Mets and prostate cancer. We believe the result is reliable for two reasons. Firstly, only longitudinal cohort studies were included in this analysis, imparting strong evidence for our conclusions. In addition, the association between MetS and prostate cancer may be affected by several factors, including heterogeneity among the individual studies. The heterogeneity may arise from differences in age, race, the definition of MetS [22], and geographic factors [26]. Further, MetS is a syndrome composed of at least 3 components, and the individual component may exert antagonistic functions on one another Thus the syndrome may represent an integrated outcome that combines neutralizing positive and negative functions. For example, a meta-analysis revealed that diabetes mellitus was significantly negatively associated with prostate cancer risk in population-based studies (RR = 0.72, 95% CI: 0.64-0.81) and cohort studies conducted in the USA (RR = 0.79, 95% CI: 0.73, 0.86) [38]. Furthermore, several genome-wide association studies suggest that diabetes mellitus and prostate cancer share certain genetic factors, including the HNF1β and JAZF1 genes, and a previous study suggested that JAZF1 might represent a potential target against diabetes and obesity [39]. Although hypertension was found to be positively associated with prostate cancer risk [33,40-42], Obesity is negatively with localized prostate cancer (0.94, 95% CI, 0.91-0.97) and positively associated with advanced prostate cancer risk (1.07, 95% CI 1.01-1.13) [43]. However, after analyses of several parameters of PCa aggressiveness and progression, we found MetS to be significantly associated with an increased risk of prostate cancer with a high-Gleason score or advanced clinical stage, with biochemical recurrence after primary treatment and with prostate cancer-specific mortality. If confirmed by more investigations, this finding may open a new research field on PCa development and progression, potentially leading to new strategies or methods for PCa treatment. MetS is a major public health problem and prostate cancer is the most prevalent solid organ tumor, accounts for 29% of all cancer cases and the second most common cause of death by cancer among men in the USA [44]. Therefore we believe that there is a compelling need to investigate this association between MetS and prostate cancer although the association is not strong. Nevertheless, the reliability of these results is limited. First, Gleason score and clinical stage data were extracted from cross-sectional studies not longitudinal cohort studies. Second, there exists a small difference among studies on the definition of high-grade Gleason PCa, some authors defined a high Gleason score ≥ 7 whereas others defined a high score as >7. Third, the pathological stage data in some studies were from biopsy not radical prostatectomy specimens. Last but not least, to date there remains limited studies focusing on this association, although many of the available studies are well designed case-control or longitudinal cohort studies. In addition to the limitations listed above, another limitation for the analyses of the association between MetS and prostate cancer risk or prostate cancer parameters is that we did not perform a meta-regression to attempt to explain the heterogeneity of the study because of the varying adjustments in the individual studies. The result of a recent meta-analysis on 9 cross-sectional studies of metabolic syndrome in adult cancer survivors increases the weight of this suspicion, as it revealed that no significant association was found for non-hematologic malignancies, including testicular tumor, prostate cancer, sarcoma, and epithelial ovarian [45]. Therefore, there is an urgent future need to confirm this association and to find potential mechanisms to explain how metabolic factors affect the development or progression of PCa.

Conclusions

Based on the current findings, MetS is not associated with prostate cancer risk, but preliminary evidences demonstrates that men with MetS more frequently suffer high-grade prostate cancer, more advanced disease and are at greater risk of progression after radical prostatectomy and prostate cancer-specific death. Together, these findings indicate that MetS may be associated with the progression of prostate cancer and adverse clinical outcomes. Further studies with adjustment for appropriate confounders and larger, prospective, multicenter investigations are required in the future.

Abbreviations

PCa: Prostate cancer; MetS: Metabolic syndrome; RR: Relative risk; OR: Odd ratio; HR: Hazard ratio; CIs: Confidence intervals.

Competing interests

No potential conflicts of interest were disclosed.

Authors’ contributions

This study was designed and supervised by XJ. Literature search, selection and data extraction was by YX and HX, and data analyses were performed by YX, HX, ZC, SJ, QX, YZ and GL. Data interpretation and manuscript writing received contributions from all authors. All authors read and approved the final manuscript.
  44 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

2.  Metabolic syndrome and pancreatic cancer risk: a case-control study in Italy and meta-analysis.

Authors:  Valentina Rosato; Alessandra Tavani; Cristina Bosetti; Claudio Pelucchi; Renato Talamini; Jerry Polesel; Diego Serraino; Eva Negri; Carlo La Vecchia
Journal:  Metabolism       Date:  2011-05-06       Impact factor: 8.694

3.  Features of the metabolic syndrome and prostate cancer in African-American men.

Authors:  Jennifer L Beebe-Dimmer; Rodney L Dunn; Aruna V Sarma; James E Montie; Kathleen A Cooney
Journal:  Cancer       Date:  2007-03-01       Impact factor: 6.860

4.  Prospective study on metabolic factors and risk of prostate cancer.

Authors:  Christel Häggström; Tanja Stocks; David Ulmert; Tone Bjørge; Hanno Ulmer; Göran Hallmans; Jonas Manjer; Anders Engeland; Gabriele Nagel; Martin Almqvist; Randi Selmer; Hans Concin; Steinar Tretli; Håkan Jonsson; Pär Stattin
Journal:  Cancer       Date:  2012-10-22       Impact factor: 6.860

5.  Blood pressure and risk of prostate cancer: Cohort Norway (CONOR).

Authors:  Richard M Martin; Lars Vatten; David Gunnell; Pål Romundstad
Journal:  Cancer Causes Control       Date:  2009-12-01       Impact factor: 2.506

6.  Components of the metabolic syndrome and risk of prostate cancer: the HUNT 2 cohort, Norway.

Authors:  Richard M Martin; Lars Vatten; David Gunnell; Pål Romundstad; Tom I L Nilsen
Journal:  Cancer Causes Control       Date:  2009-03-11       Impact factor: 2.506

Review 7.  Obesity, metabolic syndrome, and prostate cancer.

Authors:  Ann W Hsing; Lori C Sakoda; Streamson Chua
Journal:  Am J Clin Nutr       Date:  2007-09       Impact factor: 7.045

8.  Metabolic syndrome and cancer risk.

Authors:  Antonio Russo; Mariangela Autelitano; Luigi Bisanti
Journal:  Eur J Cancer       Date:  2007-12-04       Impact factor: 9.162

9.  Risk factors for prostate cancer: An hospital-based case-control study from Mumbai, India.

Authors:  B Ganesh; Sushama L Saoba; Monika N Sarade; Suvarna V Pinjari
Journal:  Indian J Urol       Date:  2011-07

10.  Prostate cancer in patients with metabolic syndrome is associated with low grade Gleason score when diagnosed on biopsy.

Authors:  Kyoung Pil Jeon; Tae Yoong Jeong; Seo Yeon Lee; Sang Won Hwang; Joong Hui Shin; Dong Suk Kim
Journal:  Korean J Urol       Date:  2012-09-19
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  35 in total

1.  Unhealthy diets: a common soil for the association of metabolic syndrome and cancer.

Authors:  Katherine Esposito; Fortunato Ciardiello; Dario Giugliano
Journal:  Endocrine       Date:  2014-01-10       Impact factor: 3.633

2.  Effect of metabolic syndrome and its components on recurrence and survival in early-stage non-small cell lung cancer.

Authors:  Ying-Sheng Wen; Xue-Wen Zhang; Rong-Qing Qin; Lan-Jun Zhang
Journal:  Med Oncol       Date:  2014-12-05       Impact factor: 3.064

3.  Metabolic syndrome, dyslipidemia and prostate cancer recurrence after primary surgery or radiation in a veterans cohort.

Authors:  L C Macleod; L J Chery; E Y C Hu; S B Zeliadt; S K Holt; D W Lin; M P Porter; J L Gore; J L Wright
Journal:  Prostate Cancer Prostatic Dis       Date:  2015-03-31       Impact factor: 5.554

Review 4.  Metabesity and urological cancers.

Authors:  Ali Atan
Journal:  Turk J Urol       Date:  2017-12-01

5.  Metabolic syndrome and total cancer mortality in the Third National Health and Nutrition Examination Survey.

Authors:  Wambui G Gathirua-Mwangi; Patrick O Monahan; Mwangi J Murage; Jianjun Zhang
Journal:  Cancer Causes Control       Date:  2017-01-17       Impact factor: 2.506

6.  Statins and Finasteride Use Differentially Modify the Impact of Metformin on Prostate Cancer Incidence in Men with Type 2 Diabetes.

Authors:  Wang Chen-Pin; Hernandez Javier; Carlos Lorenzo; John R Downs; Ian M Thompson; Bradley Pollock; Donna Lehman
Journal:  Ann Transl Med Epidemiol       Date:  2014

7.  Obesity, age, ethnicity, and clinical features of prostate cancer patients.

Authors:  Victor J Wu; Darren Pang; Wendell W Tang; Xin Zhang; Li Li; Zongbing You
Journal:  Am J Clin Exp Urol       Date:  2017-02-15

8.  Metabolic syndrome-like components and prostate cancer risk: results from the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) study.

Authors:  Katharine N Sourbeer; Lauren E Howard; Gerald L Andriole; Daniel M Moreira; Ramiro Castro-Santamaria; Stephen J Freedland; Adriana C Vidal
Journal:  BJU Int       Date:  2014-10-20       Impact factor: 5.588

Review 9.  Enhancing active surveillance of prostate cancer: the potential of exercise medicine.

Authors:  Daniel A Galvão; Dennis R Taaffe; Nigel Spry; Robert A Gardiner; Renea Taylor; Gail P Risbridger; Mark Frydenberg; Michelle Hill; Suzanne K Chambers; Phillip Stricker; Tom Shannon; Dickon Hayne; Eva Zopf; Robert U Newton
Journal:  Nat Rev Urol       Date:  2016-03-08       Impact factor: 14.432

Review 10.  Metabolic syndrome in prostate cancer: impact on risk and outcomes.

Authors:  Fatima H Karzai; Ravi A Madan; William L Dahut
Journal:  Future Oncol       Date:  2016-04-12       Impact factor: 3.404

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