The Potential Diagnostic Accuracy of Let-7 Family for Cancer: A Meta-Analysis
| Autor: | Wen-Ting Zhang, Guo-Xun Zhang, Shuai-Shuai Gao |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Technology in Cancer Research & Treatment, Vol 20 (2021) |
| Druh dokumentu: | article |
| ISSN: | 1533-0338 15330338 |
| DOI: | 10.1177/15330338211033061 |
| Popis: | Background: Cancer is a global public health problem affecting human health. Early stage of cancer diagnosis, when it is not too large and has not spread is important for successful treatment. Many researchers have proposed that the let-7 microRNA family can be used as a biomarker for cancer diagnosis. The aim of this meta-analysis is to evaluate whether let-7 family can be used as a diagnostic tool for cancer patients. Methods: We conducted a comprehensive literature search on PubMed, EMBASE, Web of Science, Cochrane Library, Google Scholar, China National Knowledge Infrastructure (CNKI) and Wanfang database, updated to October 23, 2020. A random effects model was used to pool the sensitivity and specificity. Besides, we measured the diagnostic value using positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) were pooled. In addition, meta-regression and subgroup analysis were performed to explore the possible sources of heterogeneity, and Deeks’ funnel chart was used to assess whether there was publication bias. Results: 31 studies from 15 articles were included in the current meta-analysis. The overall sensitivity, specificity, PLR, NLR, DOR and AUC were 0.80 (95% CI: 0.75-0.85), 0.81 (95% CI: 0.74-0.86), 4.2 (95% CI: 2.9-5.9), 0.24 (95% CI: 0.19-0.32), 17 (95% CI: 10-29) and 0.87 (95% CI: 0.84-0.90), respectively. Subgroup analysis shows that the let-7 family cluster of serum type showed a better diagnostic accuracy of cancer, especially the breast cancer. Although there is no publication bias, it still has some limitations. Conclusions: let-7 family can be considered as a promising non-invasive diagnostic biomarker for cancer. |
| Databáze: | Directory of Open Access Journals |
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