SynthesisBMC nephrology2025
MicroRNAs diagnostic value or IgAN: a meta-analysis.
Synthesis in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundKidney biopsy, an invasive procedure with risks such as bleeding, is currently the gold standard for IgA nephropathy (IgAN) detection. Nevertheless, it may not be available in some centres. MicroRNAs have been investigated in some investigations as possible indicators for IgAN diagnosis. This investigation will assess the diagnostic utility of microRNAs for IgAN.
methodsSeveral databases were thoroughly examined up to July 20, 2023, including Wanfang Data, Embase, PubMed, Web of Science, SINOMED, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), and Cochrane Library.We used Stata software (version 16.0) and Meta-Disc software (version 1.4) for the analysis. The negative and positive likelihood ratios (NLR and PLR), diagnostic odds ratio (DOR), pooled specificity and sensitivity were all calculated. Furthermore, the area under the curve (AUC) was computed and the summary receiver operating characteristic (SROC) curve was presented. Additionally, the Deeks funnel plot approach was employed to assess publication bias. We also used Fagan’s column-line plots to examine the clinical diagnostic utility of microRNA testing for IgAN.
resultsThe analysis comprised nine diagnostic tests in total, including 3359 individuals. The demonstrated that the pooled DOR, specificity, and sensitivity of microRNA in IgAN detection was 18.39 (95% confidence interval, CI: 11.13 to 30.39), 0.78 (95% CI: 0.76 to 0.80), and 0.80 (95% CI: 0.78 to 0.82), respectively. Moreover, an AUC of 0.83 was determined. Subgroup analysis showed that the study’s specimen type had a substantial impact on the precision of the microRNA-based IgAN diagnosis. The Deeks funnel plot (p = 0.56) showed no publication bias. Eventually, the Fagan column-line plot showed that using miRNA to diagnose IgAN improved diagnostic accuracy.
conclusionsMicroRNAs demonstrate promise as diagnostic biomarkers for IgAN, showing high sensitivity and specificity in this meta-analysis. However, further large-scale and high-quality studies are needed to validate these findings and establish their definitive clinical utility.
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