Published online Jun 30, 2007.
https://doi.org/10.4111/kju.2007.48.6.585
The Characteristics of Prostate Cancer with Metabolic Syndrome in Korean Men
Abstract
Purpose
Metabolic syndrome, a concurrence of disturbed glucose and insulin metabolism, overweight, abdominal fat distribution, dyslipidemia, and hypertension, has been reported to have some association with prostate cancer. Here, we assessed the relationship between metabolic syndrome and prostate cancer.
Materials and Methods
We assessed a total of 261 men who underwent radical retropubic prostatectomy between January 2004 and May 2005. The patients were stratified into two groups, with metabolic syndrome (n=75) or without (n=186). Metabolic syndrome was defined by the criteria of National Cholesterol Education Program Adult Treatment Panel III. We compared the clinical and pathologic features of specimens between the groups.
Results
There was no significant difference between the two groups in terms of mean age, serum prostate specific antigen level, prostate size, Gleason score, and pathologic stage. The tumor volume of prostate cancer was significantly higher in the metabolic syndrome group (6.6±5.5cc vs 5.0±4.5cc, p=0.010). No significant differences were observed in extracapsular extension, seminal vesicle invasion, bladder neck invasion, angiolymphatic invasion, perineural invasion, and multicentricity of cancer between the two groups. As the component of metabolic syndrome increased, the tumor volume was also found to increase (p-value=0.025).
Conclusions
The data from our study support that metabolic syndrome is closely associated with the development and progression of prostate cancer.
Table 1
Patient characteristics with or without metabolic syndrome (mean±SD)
Table 2
Pathologic characteristics with or without metabolic syndrome
Table 3
Comparison of age, PSA, prostatectomy Gleason score, and tumor volume according to the finding of metabolic disorder in patients
Table 4
Association between prostate cancer characteristics and the number of combined metabolic disorder
Table 5
Multivariable analysis affecting tumor volume by linear regression model
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