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. 2022 Oct 24:12:987704.
doi: 10.3389/fonc.2022.987704. eCollection 2022.

The diagnostic significance of blood-derived circRNAs in NSCLC: Systematic review and meta-analysis

Weijie Yu  1 , Ruixue Liu  2 , Zhoulin Miao  3 , Liwei Zhang  2 , Ilyar Sheyhidin  2 , Julaiti Ainiwaer  2
Affiliations

The diagnostic significance of blood-derived circRNAs in NSCLC: Systematic review and meta-analysis

Weijie Yu et al. Front Oncol. .

Abstract

Background: Using blood-derived circular RNAs (circRNAs) may be an efficient tool for noninvasive fluid biopsy in diagnosing non-small cell lung cancer (NSCLC). However, no relevant systemic meta-analysis has been conducted so far to support the diagnostic value of using blood-derived circRNAs in NSCLC clinically. The aim of this study is to clarify the issue through a meta-analysis.

Methods: A systematic search strategy was used to search relevant literature in the databases of PubMed, Web of Science, and Cochrane Library from 2017 to 2022. The relationship between the diagnostic accuracy of circRNAs and NSCLC was analyzed. For the purpose of evaluating the quality of the literature, Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used. Statistical analyses were assessed using Stata software (version 17.0) and META-DISC (version 1.4).

Results: The meta-analysis included 1,093 patients with NSCLC and 959 controls. Results are as follows: pooled sensitivity, 0.78 (95% CI = 0.71-0.83, I2 = 71.86); pooled specificity, 0.76 (95% CI = 0.70-0.82, I2 = 70.12); pooled positive likelihood ratio (PLR), 3.3 (95% CI = 2.6-4.2, I2 = 37.56); pooled negative likelihood ratio (NLR), 0.29 (95% CI = 0.23-0.37, I2 = 64.67); diagnostic odds ratio (DOR), 11.42 (95% CI = 7.88-16.56, I2 = 99.05); area under the receiver operating characteristic curve (AUC), 0.84 (95% CI = 0.80-0.87). Based on the subgroup analysis, it appears that the heterogeneity is primarily caused by the NSCLC subgroup.

Conclusion: circRNAs are highly useful diagnostic biomarkers for NSCLC in China. Further prospective studies on the diagnostic value of circRNAs should be conducted in multiple countries.

Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022323804.

Keywords: NSCLC; blood-derived; circRNAs; diagnosis; oncology.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Preferred Reporting Items for Systematic reviews and Meta Analyses (PRISMA) flowchart of the included and excluded study selection process.
Figure 2
Figure 2
Forest plots of diagnostic accuracy index and summary receiver operating characteristic (SROC) curve and Fagan’s nomogram for likelihood ratios, a likelihood ratio scattergram, publication bias. (A) Forest plots of sensitivity and specificity for circular RNAs (circRNAs) in diagnosis. (B) Forest plots of the positive likelihood ratio and negative likelihood ratio in diagnosis. (C) Forest plots of the diagnostic odds ratio in diagnosis. (D) SROC curve for circRNAs in diagnosing non-small cell lung cancer (NSCLC). (E) Fagan’s nomogram for likelihood ratios. (F) A likelihood ratio scattergram.
Figure 3
Figure 3
Sensitivity analyses for diagnosis analysis.
Figure 4
Figure 4
Publication bias analysis. (A) Egger’s publication bias plot. (B) Funnel plot. (C) Deeks’ funnel plot.
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