MetabolicSyndrome: A High Risk for Urological Malignancies? A Prospective Study
SJoseph Philipraj*, Karthik Meyappan, Vishal Shet
Department of Urology, Mahatma Gandhi Medical college and Research Institute, Pondicherry, India
*Corresponding author:S.Joseph Philipraj, Department of Urology, Mahatma Gandhi Medical college and Research Institute, Pondy-Cuddallore Main Road, Pillaiyarkuppam, Podicherry- 607402, Tamil Nadu, India. Tel:+919475919727; +919047521148; Email: josephphilipraj@gmail.com.
Received Date: 26 October, 2017; Accepted Date: 01November, 2017; Published
Date: 08November, 2017
Citation:Philipraj SJ,Meyappan K, Shet V (2017) Metabolic Syndrome: A High Risk for Urological Malignancies? A Prospective Study. J Urol Ren Dis 2017: 162. DOI: 10.29011/2575-7903.000162
1. Abstract
Metabolic syndrome is collection of risk factors for Cardiovascular disease. It is growing problem worldwide. Available evidence from epidemiologic investigations and experimental, translational, and clinical studies supports the emerging hypothesis that metabolic syndrome may be an important etiologic factor for the development and progression of certain types of cancer and also for overall cancer mortality. Urological diseases have also been linked to the metabolic syndrome. Most established aspects of the metabolic syndrome are linked to Benign Prostatic Hyperplasia (BPH) and prostate cancer. We wanted to study the correlation Between Metabolic Syndrome and urological malignancies seen in our institution. Hence this prospective cohort study is done.
2.
Keywords:Carcinoma
Penis; Carcinoma Prostate;Carcinoma Urinary Bladder;Metabolic Syndrome;Renal
Cell Carcinoma; Urological Malignancies; Upper Urinary Tract Malignancy
1. Introduction
The incidence of Urological Malignancies has been increasing globally with a change in people’s lifestyle as well as an increase in the number of patients newly diagnosed with Metabolic Syndrome. The metabolic syndrome is a cluster of risk factors for cardiovascular disease and type 2 diabetes and constitutes a growing problem worldwide[1]. These factors include obesity(particularly central adiposity), dysglycemia,raised blood pressure, elevatedtriglyceride levels, and low HDL cholesterol levels.Available evidence from epidemiologic investigations and experimental, translational, and clinical studies supports the emerging hypothesis that metabolic syndrome may be an important etiologic factor for the development and progression of certain types of cancer and also for overall cancer mortality [2]. Urological diseases have also been linked to the metabolic syndrome. Most established aspects of the metabolic syndrome are linked to Benign Prostatic Hyperplasia (BPH) and prostate cancer. Fasting plasma insulin, in particular, has been linked to BPH and incident, aggressive and lethal prostate cancer. Patients with type 2 diabetes mellitus suffer from a significantly higher risk of urological malignancies and Carcinomabladder[3,4].
The mechanisms of such an increased Cancer risk in the diabetic patients may be related to insulin resistance, hyperinsulinemia, pro inflammatory status and increased oxidative stress [3]. The metabolic syndrome has also been shown to be associated with nonprostatic urological conditions such as male hypogonadism, nephrolithiasis, overactive bladder and erectile dysfunction, although data on these conditions are still sparse. Overall, the results of studies on urological aspects of the metabolic syndrome seem to indicate that BPH and prostate cancer could be regarded as two new aspects of the metabolic syndrome, and that an increased insulin level is a common underlying aberration that promotes both BPH and clinical prostate cancer. Ethnical differences may exist when the risk of specific cancer types is compared between patients with Diabetes mellitus and individuals without Diabetes mellitus. Smoking, obesity, dyslipidemia, hypertension have been identified as potential risk factors for renal malignancy [5-7]. In diabetics, cancer contributes 13% to mortality and high rates of cancer recurrence [8]. Increasing BMI was associated with higher risk of developing invasive penile cancer[9].It is hypothesised that high circulating insulin levels indirectly drive hepatic production of insulin-like growth factor 1 and that this combined effect acts as a ‘fertiliser’, generating a microenvironment that promotes prostate tumour growth[10]. There is a growing body of evidence showing that obesity is associated with an increase in aggressive prostate cancer, increased risk of failure of radical therapy and increased prostate cancer-specific mortality [11]. Increased physical activity appears to offer a small protective effect on subsequent risk of developing prostate cancer[12-15].
2. Patients and Methods
This isa prospective study of 49 patients with Urological Malignancy who presented to our Institution between January 2016 to June 2017. Association of Metabolic Syndrome(MetS) in these patients were studied and Correlation was evaluated using statistical methods. Individuals with the following UrologicalMalignancies were included in this study: CarcinomaProstate, Renal Cell Carcinoma,Transitional Cell Carcinoma Bladder&Upper Tract, Carcinoma Penis.
Following Criteria were used for the clinical Identification of the Metabolic Syndrome -(Any 3 of the Following),
*Abdominal
obesity * Waist circumference:
Men
- >102 cm (>40 in)
Women
>88 cm (>35 in)
*Triglycerides
>150 mg/dL
*HDL
cholesterol
Men
<40 mg/dL
Women
<50 mg/dL
*Blood
pressure >130/>85 mm Hg
*Fasting
glucose >110 mg/dL
(National Cholesterol Education Program ATP III Guidelines)
FollowingVariables were studied
·
Age
·
Sex
·
H/o Smoking
·
H/o Alcoholism
·
Height in meters
·
Weight in kg
·
BMI
·
Waist circumference in inches
·
Fasting Sugars in mg/dl or diagnosed DM
on treatment
·
BP in mm of Hg or diagnosed HTN on
treatment
·
S. Triglycerides in mg/dL
· S. HDL in mg/dL
3. Results
3.1. Statistical Analysis
The
data analysis pertaining to the different cancer regions and related parameters
are reported.Frequency analysis, Descriptive summary of the clinical parameters
across cancer regions, relational understanding between clinical parameters
with respect to different malignancies, cross tabulations are reported.Along
with these outcomes, a classifier rule is built to assess the risk involved to
observing a prostate malignancy using several clinical parameters.To do so, a multinomial
logistic regression is applied, and the entire analysis is carried out in IBM
SPSS 19.0 version.All the comparisons are made at 0.05 level of significance (Table 1) (Figure 1,2).
The
comparable malignancy is Prostate and accordingly the models are developed.
With respect to Prostate and Bladder cancer, individuals who have the alcohol
intake are 2.4 times susceptible to have prostate malignancy and similarly when
we compare the Prostate and Penis Malignancy, the individuals who have the
habit of alcohol, they are observed to have risk 7 times than that of
non-alcoholic(Table 3).
These are pertaining to
Prostate cancer samples.It is obvious that, BMI and Waist circumference are
highly and positively correlated (r=0.971).In rest of the parameters, moderate
amount of correlation is noticed.Poor correlation is observed between
Triglycerides and HDL, Waist Circumference(Table 6).
4. Discussion
Of the total 49 patients in our study 17 had CarcinomaProstate, 6 had CarcinomaBladder, 8 had CarcinomaPenis, 5 had Renal Cell Carcinomaand 3 had Transitions Cell Carcinoma of the Upper Tract.In the individuals with prostate cancer, the mean age is observed to be 69.82 and it is 61.75 for the individuals diagnosed with Bladder cancer.Further, mean Triglyceride level is observed to be little higher in the individuals of Bladder cancer than that of Prostate cancer.With respect to Prostate and Bladder cancer, individuals who have the alcohol intake are 2.4 times susceptible to have prostate malignancy and similarly when we compare the Prostate and Penile Malignancy, the individuals who have the habit of alcoholconsumption, they are observed to have risk 7 times than that of non-alcoholic.
5. Conclusions
Many
adverse health consequences result from Metabolic Syndrome including the
increased risk for several cancers. Our study shows a higherincidence of
Metabolic Syndrome in patients with Urological Malignancies. Most factors
responsible for metabolic syndrome are modifiable hence greater emphasis on
Lifestyle modification and control of co-morbid conditions like Diabetes and
Hypertension may be beneficial in reducing the incidences of Urological
Malignancies over the long run.
Figure
1: Shows the various types of malignancies and their
percentage appearance in our set up.
Figure 2:Shows
the incidence of Components of Metabolic Syndrome.
Parameter |
Category |
Frequency |
Percent |
Cancer Region |
Prostate |
17 |
34.7 |
Bladder |
16 |
32.7 |
|
Penis |
8 |
16.3 |
|
RCC |
5 |
10.2 |
|
Upper Tract |
3 |
6.1 |
|
Total |
49 |
100.0 |
|
Sex |
Male |
45 |
91.8 |
Female |
4 |
8.2 |
|
Total |
49 |
100.0 |
|
Hypertension |
Yes |
26 |
53.1 |
No |
23 |
46.9 |
|
Total |
49 |
100.0 |
|
Diabetes Mellitus |
Yes |
22 |
44.9 |
No |
27 |
55.1 |
|
Total |
49 |
100.0 |
|
Infertility |
Yes |
2 |
4.1 |
No |
47 |
95.9 |
|
Total |
49 |
100.0 |
|
Yes |
28 |
57.1 |
|
No |
21 |
42.9 |
|
Total |
49 |
100.0 |
|
Smoking |
Yes |
28 |
57.1 |
No |
21 |
42.9 |
|
Total |
49 |
100.0 |
Table 1:Shows the incidence of Type of malignancy and Other factors which can be associated with the malignan
The results reported in the (Table 2).
Parameters |
Cancer Region |
|||||
Statistics |
Prostate |
Bladder |
Penis |
RCC |
Upper Tract |
|
Age |
Mean |
69.82 |
61.75 |
54.75 |
47.00 |
64.00 |
Std. Deviation |
10.120 |
12.715 |
20.141 |
13.000 |
10.817 |
|
Body Mass Index |
Mean |
29.71 |
28.69 |
29.13 |
30.00 |
28.67 |
Std. Deviation |
4.832 |
5.805 |
7.259 |
5.874 |
3.055 |
|
Waist Circumference |
Mean |
35.12 |
34.56 |
34.00 |
36.40 |
34.00 |
Std. Deviation |
5.419 |
6.377 |
8.264 |
5.595 |
4.583 |
|
Triglycerides |
Mean |
151.06 |
160.75 |
127.50 |
114.60 |
145.67 |
Std. Deviation |
44.732 |
57.676 |
36.975 |
30.892 |
48.583 |
|
HDL |
Mean |
41.00 |
40.94 |
46.38 |
45.40 |
45.67 |
Std. Deviation |
10.404 |
9.595 |
10.676 |
6.148 |
4.933 |
Table 2:Summarizes the fact about the parameters and how they vary between different malignancies.
Cancer Region |
B |
Std. Error |
Wald |
df |
Sig. |
Odds Ratio |
Lower Confidence Interval |
Upper Confidence Interval |
|
Bladder |
Intercept |
-1.28 |
0.87 |
2.18 |
1.00 |
0.14 |
0.76 |
7.60 |
|
ALCOHOL |
0.88 |
0.59 |
2.21 |
1.00 |
0.14 |
2.40 |
|||
Penis |
Intercept |
-3.77 |
1.32 |
8.09 |
1.00 |
0.00 |
1.54 |
33.56 |
|
ALCOHOL |
1.97 |
0.79 |
6.32 |
1.00 |
0.01 |
7.20 |
Table 3:The result obtained on performing the multinomial logistic regression analysis.
In the (Table 4,5).
Observed |
Predicted |
|
||
Prostate |
Bladder |
Penis |
Percent Correct |
|
Prostate |
12 |
5 |
0 |
70.60% |
Bladder |
8 |
8 |
0 |
50.00% |
Penis |
2 |
6 |
0 |
0.00% |
Overall Percentage |
53.70% |
46.30% |
0.00% |
48.80% |
Table 4:Confusion matrix and on the whole, using the obtained model, around 48.8% of accuracy is observed in predicting the malignancy status of an individual.
Parameters |
Response |
Cancer Region |
|||||||||
Prostate |
Bladder |
Penis |
RCC |
Upper Tract |
|||||||
Count |
Column N % |
Count |
Column N % |
Count |
Column N % |
Count |
Column N % |
Count |
Column N % |
||
Hypertension |
Yes |
10 |
58.80% |
9 |
56.30% |
3 |
37.50% |
2 |
40.00% |
2 |
66.70% |
No |
7 |
41.20% |
7 |
43.80% |
5 |
62.50% |
3 |
60.00% |
1 |
33.30% |
|
Diabetes Mellitus |
Yes |
9 |
52.90% |
8 |
50.00% |
3 |
37.50% |
1 |
20.00% |
1 |
33.30% |
No |
8 |
47.10% |
8 |
50.00% |
5 |
62.50% |
4 |
80.00% |
2 |
66.70% |
|
Infertility |
Yes |
0 |
0.00% |
0 |
0.00% |
0 |
0.00% |
2 |
40.00% |
0 |
0.00% |
No |
17 |
100.00% |
16 |
100.00% |
8 |
100.00% |
3 |
60.00% |
3 |
100.00% |
|
Alcohol Intake |
Yes |
12 |
70.60% |
8 |
50.00% |
2 |
25.00% |
4 |
80.00% |
2 |
66.70% |
No |
5 |
29.40% |
8 |
50.00% |
6 |
75.00% |
1 |
20.00% |
1 |
33.30% |
|
Smoking |
Yes |
9 |
52.90% |
9 |
56.30% |
5 |
62.50% |
3 |
60.00% |
2 |
66.70% |
No |
8 |
47.10% |
7 |
43.80% |
3 |
37.50% |
2 |
40.00% |
1 |
33.30% |
Table 5: Shows the incidence of Various components of metabolic syndrome with urological malignancies.
Cancer type = Prostate |
Body Mass Index |
Waist Circumference |
Triglycerides |
HDL |
|
Body Mass Index |
Pearson Correlation |
1 |
.971** |
.450 |
-.444 |
Sig. (2-tailed) |
.000 |
.070 |
.074 |
||
Waist Circumference |
Pearson Correlation |
.971** |
1 |
.381 |
-.411 |
Sig. (2-tailed) |
.000 |
.132 |
.101 |
||
Triglycerides |
Pearson Correlation |
.450 |
.381 |
1 |
-.228 |
Sig. (2-tailed) |
.070 |
.132 |
.379 |
||
HDL |
Pearson Correlation |
-.444 |
-.411 |
-.228 |
1 |
Sig. (2-tailed) |
.074 |
.101 |
.379 |
Table 6:The correlation values depict the inter dependency between the clinical parameters.
In(Table7),
Cancer Type=Bladder |
Body Mass Index |
Waist Circumference |
Triglycerides |
HDL |
|
Body Mass Index |
Pearson Correlation |
1 |
.976** |
.271 |
-.426 |
Sig. (2-tailed) |
.000 |
.310 |
.099 |
||
Waist Circumference |
Pearson Correlation |
.976** |
1 |
.313 |
-.360 |
Sig. (2-tailed) |
.000 |
.238 |
.171 |
||
Triglycerides |
Pearson Correlation |
.271 |
.313 |
1 |
-.679** |
Sig. (2-tailed) |
.310 |
.238 |
.004 |
||
HDL |
Pearson Correlation |
-.426 |
-.360 |
-.679** |
1 |
Sig. (2-tailed) |
.099 |
.171 |
.004 |
Table 7:The correlation values depict the inter dependency between the clinical parameters for Bladder cancer samples, moderate amount of correlation is noticed between BMI and HDL, Waist circumference and Triglycerides. Good amount of relation (negative) is observed between Triglycerides and HDL. In (Table 8)
Body Mass Index |
Waist Circumference |
Triglycerides |
HDL |
||
Body Mass Index |
Pearson Correlation |
1 |
.974** |
.672 |
-.843** |
Sig. (2-tailed) |
.000 |
.068 |
.009 |
||
Waist Circumference |
Pearson Correlation |
.974** |
1 |
.575 |
-.805* |
Sig. (2-tailed) |
.000 |
.136 |
.016 |
||
Triglycerides |
Pearson Correlation |
.672 |
.575 |
1 |
-.837** |
Sig. (2-tailed) |
.068 |
.136 |
.010 |
||
HDL |
Pearson Correlation |
-.843** |
-.805* |
-.837** |
1 |
Sig. (2-tailed) |
.009 |
.016 |
.010 |
Table 8: The correlation values depict the inter dependency between the clinical parameters for Penis malignancy samples, Significant correlation values are observed between almost all pairs of parameters. HDL and BMI are highly and negatively correlated, BMI and Triglycerides are moderately correlated with positive magnitude, HDL and Waist circumference are related to a maximum extent in negative magnitude. Similar sort of negative relation is noticed between HDL and Triglycerides.