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Association between insulin-like growth factor-binding protein-3 polymorphism -202 A/C and the risk of prostate cancer: a meta-analysis

Authors Qin Z, Li X, Tang J, Jiang X, Yu Y, Wang C, Xu W, Hua Y, Yu B, Zhang W

Received 2 March 2016

Accepted for publication 20 June 2016

Published 6 September 2016 Volume 2016:9 Pages 5451—5459

DOI https://doi.org/10.2147/OTT.S107595

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Manfred Beleut

Peer reviewer comments 4

Editor who approved publication: Dr William Cho


Zhiqiang Qin,1,2,* Xiao Li,1,* Jingyuan Tang,2,* Xuping Jiang,2 Yajie Yu,2 Chengming Wang,2 Weizhang Xu,3,4 Yibo Hua,2 Bin Yu,1 Wei Zhang2

1Department of Urologic Surgery, The Affiliated Cancer Hospital of Jiangsu Province of Nanjing Medical University, 2Department of Urology, The First Affiliated Hospital of Nanjing Medical University, 3Department of Thoracic Surgery, The Affiliated Cancer Hospital of Jiangsu Province of Nanjing Medical University, 4Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Cancer Institute of Jiangsu Province, People’s Republic of China

*These authors contributed equally to this work

Background: Some previous studies have investigated the relationship between insulin-like growth factor-binding protein-3 polymorphism and prostate cancer (PCa) susceptibility; however, the findings from those studies remain inconsistent. Hence, the aim of this meta-analysis was to provide a more reliable conclusion about such associations.
Methods: A meta-analysis based on twelve studies was conducted, and 8,341 PCa cases and 7,734 controls were included in this analysis. All relevant studies published till February 1, 2016, were identified by searching the databases such as PubMed, EMBASE, and Web of Science. Data were pooled by odds ratios (ORs) with 95% confidence intervals (CIs) in order to assess the strength of such associations. Publication bias was evaluated using Begg’s funnel plots and Egger’s regression test.
Results: Several articles provided data only for particular genotypes; therefore, only dominant model analyses were carried out for all of these studies. Initially, the results from this analysis indicated that rs2854744 was not associated with PCa susceptibility (OR =1.12, 95% CI =0.996–1.2). However, after excluding one study due to its heterogeneity and publication bias, a significant relationship was detected between rs2854744 and PCa risk (OR =1.10, 95% CI =1.03–1.17). When stratified by genotyping method, significant results were detected only in the Sequenom method group (OR =1.13, 95% CI =1.04–1.22). Moreover, the results from a subgroup analysis that was conducted by using source of controls were significant only in the population-based control group.
Conclusion: This meta-analysis suggested that the insulin-like growth factor-binding protein-3 polymorphism -202 A/C was associated with PCa susceptibility.

Keywords: IGFBP3, gene polymorphism, prostate cancer, meta-analysis

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