Ontology highlight
ABSTRACT: Background
The association between serum C-peptide concentration and prostate cancer remains unexplored. Therefore, we conducted a meta-analysis to assess whether C-peptide serum concentrations are associated with increased prostate cancer risk.Methods
Several databases were searched to identify relevant original research articles published before November 2017. Random-effects models were used to summarize the overall estimate of the multivariable-adjusted odds ratios (ORs) with 95% confidence intervals (CIs).Results
Nine observational studies involving 11,796 participants were identified. The findings of the meta-analysis indicated that the association between serum C-peptide concentration and prostate cancer was not significant (OR: 1.15, 95% CI: 0.85-1.54; for highest versus lowest category C-peptide concentrations, P = .376). The associations were inconsistent, as indicated by subgroup analyses.Conclusion
Although our findings provided no support for the hypothesis that serum C-peptide concentration is associated with excess risk of prostate cancer, people must pay attention to this aspect and increase physical activity or modify dietary habits to constrain insulin secretion, which possibly lead to decreased incidence of prostate cancer. Hence, well-designed observational studies involving different ethnic populations are still needed.
SUBMITTER: Guo ZL
PROVIDER: S-EPMC6081093 | biostudies-literature | 2018 Aug
REPOSITORIES: biostudies-literature
Guo Zhen-Lang ZL Weng Xiang-Tao XT Chan Franky-Leung FL Gong Lei-Liang LL Xiang Song-Tao ST Gan Shu S Gu Chi-Ming CM Wang Shu-Sheng SS
Medicine 20180801 31
<h4>Background</h4>The association between serum C-peptide concentration and prostate cancer remains unexplored. Therefore, we conducted a meta-analysis to assess whether C-peptide serum concentrations are associated with increased prostate cancer risk.<h4>Methods</h4>Several databases were searched to identify relevant original research articles published before November 2017. Random-effects models were used to summarize the overall estimate of the multivariable-adjusted odds ratios (ORs) with ...[more]