CircRNAs as promising biomarker in diagnostic and prognostic of lung cancer: An updated meta-analysis

As a class of endogenous non-coding RNAs with closed-loop structure, circular RNAs (circRNAs) are receiving more and more attention. CircRNAs have been reported to be widely expressed in various human cancers and are implicated in tumorigenesis and progression. The present study aimed to systematically evaluate the clinicopathological, diagnostic and prognostic values of circRNAs in lung cancer. We searched literature from PubMed, Web of science, Cochrane Library, EMBASE and Ovid online databases up to May 29, 2020. Statistical analyses were undertaken based on Stata 11.0, Meta-DiSc 1.4, and RevMan 5.3 software. Finally, a total of 63 eligible articles were included in our meta-analysis, including 18 studies for diagnosis, 22 studies for prognosis and 57 studies for clinicopathological features. In terms of diagnostic values, circRNAs could discriminate between lung cancer patients and the normal individuals with a relatively high pooled area under the curve (AUC) of 0.83 (95%CI, 0.80–0.86). For the prognostic values, we found that elevated expression of oncogenic circRNAs could predict poor survival outcomes based on multivariate analysis (HR = 2.430, 95%CI = 2.003–2.948, P