LncRNA as a diagnostic marker for rheumatoid arthritis: a systematic review and meta-analysis
Abstract
Background/aims: Rheumatoid arthritis (RA) is categorized as an autoimmune disorder characterized by the absence of a definitive cure. In this investigation, we executed a systematic review and diagnostic meta-analysis to ascertain the diagnostic efficacy of long non-coding RNAs (lncRNAs) in the identification of RA.
Methods: Our survey involved relevant studies published in PubMed, Web of Science, Embase, Cochrane library search engines. Specificity and sensitivity were calculated, as well as positive likelihood ratios (PLRs), negative likelihood ratios (NLRs), and diagnostic odds ratios (DORs). The operating characteristics of the overall receiver were plotted, and the area under the curve (AUC) was evaluated.
Results: This systematic review and meta-analysis incorporated 34 studies involving a total of 1,535 participants-comprising 853 individuals diagnosed with RA and 682 control subjects without the disease. The pooled specificity, sensitivity, NLR, PLR, and DOR were 0.88 (95% CI: 0.84-0.92), 0.86 (95% CI: 0.81-0.91), 0.15 (95% CI: 0.11-0.22), 7.51 (95% CI: 5.39-10.46), and 49.06 (95% CI: 30.31-79.41), respectively, and the AUC = 0.94 (95% CI: 0.91-0.96). Subgroup analysis was performed according to lncRNA expression in RA, sample size, sample type, RNA extraction, and control group type.
Conclusion: This meta-analysis reveals that lncRNAs may serve as powerful biomarkers for RA. This systematic review and meta-analysis provides the first evidence showing the potential…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,535 participants or records.
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