SynthesisBiomedical engineering online2025
Unveiling the diagnostic power of lncRNAs in colorectal cancer: a meta-analysis.
Synthesis in Biomedical engineering online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.Journal of imaging informatics in medicine · 2026Review
- Unleashing lncRNA THOR: roles in cancer progression and clinical outlook.Molecular genetics and genomics : MGG · 2026Review
- Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.Journal of personalized medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundColorectal cancer (CRC) is a highly aggressive and extensive malignancy. Although long noncoding RNAs (lncRNAs) are often used as diagnostic biomarkers, their diagnostic effectiveness in CRC remains uncertain.
methodsFrom January 1, 2015, to April 1, 2024, we conducted a comprehensive search of Embase, China National Knowledge Infrastructure (CNKI), Wanfang, PubMed, Cochrane Library, and Web of Science (WoS). The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the receiver operating characteristic curve (AUC) and Fagan plot analysis were used to assess the overall test performance of lncRNAs. Moreover, we evaluated the publication bias using the Deeks' funnel plot asymmetry test.
resultsTwenty-eight publications were identified and incorporated into this meta-analysis. The aggregated diagnostic data were as follows: The pooled sensitivity was 0.79 (95% CI, 0.75-0.83). The pooled specificity was 0.81 (95% CI, 0.78-0.84). The PLR was 3.68 (95% CI, 3.18-4.26). The NLR was 0.28 (95% CI, 0.24-0.33). The DOR was 15.01 (95% CI, 11.85-19.00). The AUC was 0.87 (95% CI, 0.84-0.90). Deeks' funnel plot asymmetry test indicated no significant evidence of publication bias (p > 0.05). The Fagan plot analysis showed that the post-test probability was 81% for positive results and 20% for negative results. Univariate meta-regression identified multiple sources of heterogeneity in the data, including year, sample size and specimen.
conclusionIn summary, our findings demonstrate that lncRNAs have a promising diagnostic accuracy for CRC, underscoring their potential as effective non-invasive biomarkers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.