University of Hertfordshire

From the same journal

From the same journal

By the same authors

Documents

View graph of relations
Original languageEnglish
Article numbere46691
JournalPLoS ONE
Volume7
Issue10
DOIs
Publication statusPublished - 1 Oct 2012

Abstract

Background: Emerging evidence suggests that statins may decrease the risk of cancers. However, available evidence on prostate cancer (PCa) is conflicting. We therefore examined the association between statin use and risk of PCa by conducting a detailed meta-analysis of all observational studies published regarding this subject. Methods: Literature search in PubMed database was undertaken through February 2012 looking for observational studies evaluating the association between statin use and risk of PCa. Before meta-analysis, the studies were evaluated for publication bias and heterogeneity. Pooled relative risk (RR) estimates and 95% confidence intervals (CIs) were calculated using random-effects model (DerSimonian and Laird method). Subgroup analyses, sensitivity analysis and cumulative meta-analysis were also performed. Results: A total of 27 (15 cohort and 12 case-control) studies contributed to the analysis. There was heterogeneity among the studies but no publication bias. Statin use significantly reduced the risk of both total PCa by 7% (RR 0.93, 95% CI 0.87-0.99, p = 0.03) and clinically important advanced PCa by 20% (RR 0.80, 95% CI 0.70-0.90, p<0.001). Long-term statin use did not significantly affect the risk of total PCa (RR 0.94, 95% CI 0.84-1.05, p = 0.31). Stratification by study design did not substantially influence the RR. Furthermore, sensitivity analysis confirmed the stability of results. Cumulative meta-analysis showed a change in trend of reporting risk from positive to negative in statin users between 1993 and 2011. Conclusions: Our meta-analysis provides evidence supporting the hypothesis that statins reduce the risk of both total PCa and clinically important advanced PCa. Further research is needed to confirm these findings and to identify the underlying biological mechanisms.

ID: 15412942