Literature DB >> 17119028

A meta-analysis of diabetes mellitus and the risk of prostate cancer.

Jocelyn S Kasper1, Edward Giovannucci.   

Abstract

BACKGROUND: Studies investigating the association between diabetes mellitus and prostate cancer have reported inconsistent findings. We examined this association by conducting a detailed meta-analysis of the studies published on the subject.
METHODS: MEDLINE and EMBASE databases and bibliographies of retrieved articles were searched. Studies investigating the relationship between diabetes mellitus and prostate cancer were included in the meta-analysis. Potential sources of heterogeneity between studies were explored and publication bias was evaluated. Pooled relative risk (RR) was calculated using the random-effects model. Numerous relevant subgroup analyses were also done.
RESULTS: We included 19 studies, published between 1971 and 2005, in the meta-analysis and found an inverse association between diabetes mellitus and prostate cancer [RR, 0.84, 95% confidence interval (CI), 0.76-0.93, P for heterogeneity <or= 0.01]. For cohort studies alone, the RR was 0.81 (95% CI, 0.71-0.92, P for heterogeneity <or= 0.01) and for case-control studies alone, the RR was 0.89 (95% CI, 0.72-1.11, P for heterogeneity = 0.02). The significant heterogeneity was mitigated in some of the subgroup analyses. For studies conducted before prostate-specific antigen screening was introduced as a common procedure, the RR was 0.94 (95% CI, 0.85-1.03, P for heterogeneity = 0.15), and for studies conducted after this time, the RR was 0.73 (95% CI, 0.64-0.83, P for heterogeneity = 0.10). For studies that adjusted for three or more potential confounders, the RR was 0.74 (95% CI, 0.65-0.85, P for heterogeneity = 0.06) and for studies that adjusted for less than three potential confounders, the RR was 0.93 (95% CI, 0.86-1.02, P for heterogeneity = 0.18).
CONCLUSION: This study suggests an inverse relationship between diabetes and prostate cancer. Potential biological mechanisms underlying this association, as well as possible biases, are discussed.

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Mesh:

Year:  2006        PMID: 17119028     DOI: 10.1158/1055-9965.EPI-06-0410

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.254


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