Tumor Biology

, Volume 35, Issue 12, pp 12245–12253 | Cite as

Analysis of circulating microRNA biomarkers for breast cancer detection: a meta-analysis

  • Lihua Liu
  • Shan Wang
  • Xiutang Cao
  • Jianchao Liu
Research Article


Circulating microRNAs (miRNAs) have been reported to be aberrantly expressed in patients with breast cancer (BC) and thus may serve as potential diagnostic biomarkers. This meta-analysis aimed to assess the potential diagnostic value of using circulating miRNAs for BC. The summary receiver operator characteristic (SROC) curve was used to assess the overall diagnostic performance of circulating miRNA. All analyses were performed using STATA 12.0 software. Thirty-one studies from 16 publications with a total of 1,668 BC patients and 1,111 healthy controls were included in this meta-analysis. Our results showed that the pooled sensitivity (SEN) for miRNAs assays was 0.77 (95 % CI 0.69–0.84), specificity (SPE) was 0.88 (95 % CI 0.79–0.93), positive likelihood ratio (PLR) was 4.2 (95 % CI 3.0–6.0), negative LR (NLR) was 0.29 (95 % CI 0.21–0.40), and diagnostic odds ratio (DOR) was 18 (95 % CI 10–32). The area under the SROC curve (AUC) was 0.89 (95 % CI 0.86–0.91). Subgroup analysis suggested that employing a combination of multiple miRNAs was better than using a single miRNA in SEN (0.88 vs. 0.69), SPE (0.88 vs. 0.89), PLR (6.3 vs. 3.3), NLR (0.14 vs. 0.41), DOR (48 vs. 10), and AUC (0.94 vs. 0.83). In conclusion, our meta-analysis suggested that the expression profiles of circulating miRNAs, especially using a combination of them, have potential to facilitate accurate breast tumor detection. However, there are still challenges that need to be addressed to establish these new biomarkers before they can be applied to routine clinical procedures.


Circulating MicroRNAs Breast cancer Meta-analysis Diagnosis 


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Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2014

Authors and Affiliations

  • Lihua Liu
    • 1
  • Shan Wang
    • 2
  • Xiutang Cao
    • 1
  • Jianchao Liu
    • 1
  1. 1.Institute of Hospital Management and ResearchChinese PLA General HospitalBeijingChina
  2. 2.Department of Epidemiology and Biostatistics, Institute of Basic MedicinePeking Union Medical College/Chinese Academy of Medical SciencesBeijingChina

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