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Prognostic Role of MicroRNA-210 in Various Carcinomas: A Systematic Review and Meta-Analysis
Objective. Many studies have shown that microRNAs (miRNAs) could play a potential role as prognostic biomarkers of tumors. The aim of this study is to summarize the global predicting role of microRNA-210 (miR-210) for survival in patients with a variety of carcinomas. Methods. Relevant literature wa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3925626/ https://www.ncbi.nlm.nih.gov/pubmed/24591754 http://dx.doi.org/10.1155/2014/106197 |
Sumario: | Objective. Many studies have shown that microRNAs (miRNAs) could play a potential role as prognostic biomarkers of tumors. The aim of this study is to summarize the global predicting role of microRNA-210 (miR-210) for survival in patients with a variety of carcinomas. Methods. Relevant literature was identified using PubMed and the information in eligible studies has been extracted. Then meta-analysis of hazard ratio (HR) was performed to evaluate the prognostic role of the miR-210 in different tumors. Results. This meta-analysis included 9 published studies dealing with various carcinomas. For recurrence free survival or disease free survival (RFS/DFS), the combined hazard ratio (HR) and 95% confidence interval (95% CI) of higher miR-210 expression were 2.47 [1.36, 4.46], which could significantly predict poor survival in general carcinomas. MicroRNA-210 was also a significant predictor for overall survival (OS), metastasis free survival or distant relapse free survival (MFS/DRFS), and disease specific survival (DSS). Importantly, subgroup analysis suggested that higher expression of miR-210 correlated with worse RFS/DFS, OS, and MFS/DRFS, especially in breast cancer, which were 3.36 [2.30, 4.93], 3.29 [1.65, 6.58], and 2.85 [1.76, 4.62] separately. Conclusion. Our studies suggested that microRNA-210 could predict the outcome of patients with varieties of tumors, especially in breast cancers. |
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