ObjectiveTo evaluate the association between chronic opioid use for non-cancer pain and fracture risk by conducting a meta-analysis of cohort studies.MethodsCohort studies were identified by searching PubMed and EMBASE from their inception to July 2014. A fracture was considered an endpoint. The information was extracted by two authors independently. When the heterogeneity was significant, a random-effects model was used to calculate the overall pooled risk estimates.ResultsEight cohort studies were included in the final meta-analysis. On the basis of the Newcastle-Ottawa Scale (NOS), six studies were considered to be of high quality. The overall combined relative risk for the use of opioids and fractures was 1.88 (95% confidence interval [CI] 1.51-2.34). A subgroup analysis revealed the sources of heterogeneity. The sensitivity analysis indicated stable results, and no publication bias was observed.ConclusionsThis meta-analysis of cohort studies demonstrates that opioids significantly increase the risk of fractures.

BackgroundColon adenocarcinoma mostly happens at the junction of the rectum and is a common gastrointestinal malignancy. Accumulated evidence has indicated that colon adenocarcinoma develops by genetic alterations and is a complicated disease. The aim of this study was to screen differentially expressed miRNAs (DEMs) and genes with diagnostic and prognostic potentials in colon adenocarcinoma.Material/MethodsIn this study we screened DEMs and their target genes (DEGs) between 100 colon adenocarcinoma and normal samples in The Cancer Genome Atlas (TCGA) database by using the DEseq toolkit in Bioconductor. Then Go enrichment and KEGG pathway analysis were performed on the selected differential genes by use of the DAVID online tool. A regulation network of miRNA-gene was constructed and analyzed by Cytoscape. Finally, we performed ROC analysis of 8 miRNAs and ROC curves were drawn.ResultsA total of 159 DEMs and 1921 DEGs were screened, and 1881 pairs of miRNA-target genes with significant negative correlations were also obtained. A regulatory network of miRNA-gene, including 60 cancer-related genes and 47 miRNAs, was successfully constructed. In addition, 5 clusters with several miRNAs regulating a set of target genes simultaneously were identified through cluster analysis. There were 8 miRNAs involved in these 5 clusters, and these miRNAs could serve as molecular biomarkers to distinguish colon adenocarcinoma and normal samples indicated by ROC analysis.ConclusionsThe identified 8 miRNAs were closely associated with colon adenocarcinoma, which may have great clinical value as diagnostic and prognostic biomarkers and provide new ideas for targeted therapy.

Abstract