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Updated: Jun 18, 2025
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Published on: September 18, 2013
Association between the metabolic score for insulin resistance and prostate cancer: a cross-sectional study in
Jinru Wang1, Aireti Apizi2, Ning Tao1
1College of Public Health, Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, China.
Background:
Insulin resistance is associated with the development and progression of various cancers. However, the epidemiological evidence for the association between insulin resistance and prostate cancer is still limited.
Objectives:
To investigate the associations between insulin resistance and prostate cancer prevalence.
Methods:
A total of 451 patients who were pathologically diagnosed with prostate cancer in the First Affiliated Hospital of Xinjiang Medical University were selected as the case population; 1,863 participants who conducted physical examinations during the same period were selected as the control population. The metabolic score for insulin resistance (METS-IR) was calculated as a substitute indicator for evaluating insulin resistance. The Chi-square test and Mann-Whitney U test were performed to compare the basic information of the case population and control population. Univariate and multivariate logistic regression analyses to define factors that may influence prostate cancer prevalence. The generalized additive model (GAM) was applied to fit the relationship between METS-IR and prostate cancer. Interaction tests based on generalized additive model (GAM) and contour plots were also carried out to analyze the interaction effect of each factor with METS-IR on prostate cancer.
Results:
METS-IR as both a continuous and categorical variable suggested that METS-IR was negatively associated with prostate cancer prevalence. Smoothed curves fitted by generalized additive model (GAM) displayed a nonlinear correlation between METS-IR and prostate cancer prevalence (P < 0.001), and presented that METS-IR was negatively associated with the odds ratio (OR) of prostate cancer. The interaction based on the generalized additive model (GAM) revealed that METS-IR interacted with low-density lipoprotein cholesterol (LDL-c) to influence the prostate cancer prevalence (P = 0.004). Contour plots showed that the highest prevalence probability of prostate cancer was achieved when METS-IR was minimal and low-density lipoprotein cholesterol (LDL-c) or total cholesterol (TC) was maximal.
Conclusions:
METS-IR is nonlinearly and negatively associated with the prevalence of prostate cancer. The interaction between METS-IR and low-density lipoprotein cholesterol (LDL-c) has an impact on the prevalence of prostate cancer. The study suggests that the causal relationship between insulin resistance and prostate cancer still needs more research to confirm.
