Trial reportScientific reports2022
MicroRNome analysis generates a blood-based signature for endometriosis.
Trial report in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06100471 (Evaluation of Genetic Signature in Endometriosis Disease by Non Invasive Sampling), which is not on this map. Cited by 29 papers, 2 of them syntheses that pooled it.
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.
Evaluation of Genetic Signature in Endometriosis Disease by Non Invasive Sampling
Who cites it
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic accuracy of machine learning for endometriosis: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Exploring the Effects of Endocrine-Disrupting Chemicals and miRNA Expression in the Pathogenesis of Endometriosis by Unveiling the Pathways: a Systematic Review.Reproductive sciences (Thousand Oaks, Calif.) · 2024Pooled it
- Steroid hormone profiling reveals altered adrenal androgen production in endometriosis.European journal of endocrinology · 2026Article
- Translational Assessment of Omics Approaches in Endometriosis: Bridging Molecular Discovery with Clinical Utility.International journal of molecular sciences · 2026Review
- Hormonal Dysregulation and Neuroinflammation in Endometriosis: Convergent Druggable Pathways.Current issues in molecular biology · 2026Review
- Integrating Metabolic and MicroRNA Profiling to the Diagnostics of Endometriosis: A Pilot Study.International journal of molecular sciences · 2026Article
- Serum miRNA-based diagnostic models for endometriosis: from discovery to validation.Human reproduction (Oxford, England) · 2026Article
- Diagnostic discrepancies and clinical value of second medical opinions (SMO) for endometriosis: a nationwide study analysis.BMC women's health · 2025Observational
- A novel miR-4536-3p inhibition ameliorates Alzheimer's disease by reducing Aβ accumulation and tau phosphorylation.Alzheimer's research & therapy · 2025Article
- Review
- Limitations and perspectives of the novel salivary test for endometriosis: an open web-based survey study of German gynecologic healthcare providers.Archives of gynecology and obstetrics · 2025Article
- Leveraging epigenetic aberrations in the pathogenesis of endometriosis: from DNA methylation to non-coding RNAs.Frontiers in genetics · 2025Review
- miRNA expression haplotype in Hispanics with endometriosis.Frontiers in reproductive health · 2025Article
- A Comprehensive Review of Advanced Diagnostic Techniques for Endometriosis: New Approaches to Improving Women's Well-Being.Medicina (Kaunas, Lithuania) · 2024Review
- Circulating Serum Micro-RNA as Non-Invasive Diagnostic Biomarkers of Endometriosis.Biomedicines · 2024Article
- Artificial Intelligence in the Management of Women with Endometriosis and Adenomyosis: Can Machines Ever Be Worse Than Humans?Journal of clinical medicine · 2024Review
- Transcriptomic changes in eutopic endometrium and ectopic lesions during endometriosis progression in a mouse model.F&S science · 2024Article
- Circulating microRNAs as Non-Invasive Biomarkers in Endometriosis Diagnosis-A Systematic Review.Biomedicines · 2024Review
- Plasma microRNA expression in adolescents and young adults with endometriosis: the importance of hormone use.Frontiers in reproductive health · 2024Article
- Selection of reference miRNAs for RT-qPCR assays in endometriosis menstrual blood-derived mesenchymal stem cells.PloS one · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Endometriosis, characterized by endometrial-like tissue outside the uterus, is thought to affect 2-10% of women of reproductive age: representing about 190 million women worldwide. Numerous studies have evaluated the diagnostic value of blood biomarkers but with disappointing results. Thus, the gold standard for diagnosing endometriosis remains laparoscopy. We performed a prospective trial, the ENDO-miRNA study, using both Artificial Intelligence (AI) and Machine Learning (ML), to analyze the current human miRNome to differentiate between patients with and without endometriosis, and to develop a blood-based microRNA (miRNA) diagnostic signature for endometriosis. Here, we present the first blood-based diagnostic signature obtained from a combination of two robust and disruptive technologies merging the intrinsic quality of miRNAs to condense the endometriosis phenotype (and its heterogeneity) with the modeling power of AI. The most accurate signature provides a sensitivity, specificity, and Area Under the Curve (AUC) of 96.8%, 100%, and 98.4%, respectively, and is sufficiently robust and reproducible to replace the gold standard of diagnostic surgery. Such a diagnostic approach for this debilitating disorder could impact recommendations from national and international learned societies.
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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.