SynthesisBMC medical genomics2023
Diagnostic accuracy of circular RNA for diabetes Mellitus: a systematic review and diagnostic Meta-analysis.
Synthesis in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Unveiling the diagnostic power of lncRNAs in colorectal cancer: a meta-analysis.Biomedical engineering online · 2025Pooled it
- Circular RNAs: Unlocking new avenues in cardiometabolic disease management.The Journal of physiology · 2026Review
- From In Silico to Clinic: Harnessing Noncoding RNAs for Diabetes Research and Therapy, a Step toward ncRNA Precision.ACS pharmacology & translational science · 2026Review
- Circular RNAs as diagnostic biomarkers in type 2 diabetes mellitus: implications in metabolic dysfunction and immune-inflammatory crosstalk.Frontiers in immunology · 2026Review
- The therapeutic potential of circular RNAs.Nature reviews. Genetics · 2025Review
- Metabolomic signature between diabetic and non-diabetic obese patients: A protocol for systematic review.PloS one · 2024Article
- Profiling of patients with type 2 diabetes based on medication adherence data.Frontiers in public health · 2023Article
- RNA-based diagnostic innovations: A new frontier in diabetes diagnosis and management.Diabetes & vascular disease researchReview
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aimed to investigate the pooled diagnostic ability of circular RNA (circRNA) molecules for diabetes mellitus.
methodsWe searched PubMed, Scopus, and Web of Science for relevant studies. A total of 2070 participants, including 775 diabetic patients and 1295 healthy individuals, from five studies were included in this meta-analysis. True positive, true negative, false positive, and false negative data were extracted to calculate pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristics curve. The Deeks' funnel plot was applied for publication bias assessment, Cochran's Q test and I2 index were applied for inter-study heterogeneity assessment. Besides, a subgroup analysis was performed for determining the source of heterogeneity between studies. P value < 0.05 was considered significance. All analysis were done by STATA version 14.
resultsCircRNA presented a sensitivity of 76% (95% confidence interval [95%CI]: 66-84%), specificity of 77% (95%CI: 58-89%), positive LR of 3.25 (95%CI: 1.69-6.23), negative LR of 0.31 (95%CI: 0.21-0.46), DOR of 10.41 (95%CI: 4.26-25.41), and AUC of 0.82 (95%CI: 0.79-0.85) for diabetes mellitus detection. More specifically, hsa_circ_0054633 showed a sensitivity of 67% (95%CI: 53-81%) and a specificity of 82% (95%CI: 63-100%).
conclusionCircRNAs show highly accurate diagnostic capability for type 2 diabetes mellitus and gestational diabetes mellitus. High sensitivity of circRNAs introduces them as potential noninvasive biomarkers for early diagnosis of diabetes mellitus and their high specificity introduces them as potential therapeutic targets by regulation of their expression.
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