The Korean journal of internal medicine · 2026
LncRNA as a diagnostic marker for rheumatoid arthritis: a systematic review and meta-analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод в очереди
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Luo Lin-Ling, Chen Yu-Tong, Xu Yi-Ning, Lu Miao, Liu Xi-de
Аннотация
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 value of using lncRNAs as a diagnostic tool for 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 value of using lncRNAs as a diagnostic tool for RA.