{"paper_id":"3c31b1ff-e3eb-42ce-9e1b-84f4545e46b4","body_text":"Validation of a Saliva Micro–RNA Signature for Endometriosis\nPublished October 28, 2025\nNEJM Evid 2025;4(11)\nDOI: 10.1056/EVIDoa2400195\nAbstract\nBackground\nDiagnosis of endometriosis is a challenge. The recent development of a saliva-based micro–ribonucleic acid (miRNA) signature for the diagnosis of endometriosis may enable a timelier and less invasive approach, but this requires external validation.\nMethods\nThe prospective, multicenter validation of the salivary miRNA signature of endometriosis (ENDOmiRNA) study aimed to assess the diagnostic accuracy, validate the biological reproducibility, and evaluate the clinical utility of a saliva miRNA signature of endometriosis. The study population comprised patients 18 to 43 years of age with signs and symptoms suggestive of endometriosis, who were recruited from diverse medical settings. Patients received a diagnosis of endometriosis by imaging, laparoscopic procedure, or both. All patients who were determined to not have endometriosis were classified as controls (and all underwent laparoscopy). Assessment of endometriosis status based on the saliva miRNA signature was established blinded to patients’ endometriosis status, as determined by imaging and/or laparoscopy and/or histology.\nResults\nThe external validation population was composed of 971 patients, including patients from a prior interim analysis, with an overall endometriosis prevalence of 77%. The saliva miRNA signature had an accuracy (defined as the probability of correct classification for both positive and negative results) of 96.6% (95% confidence interval [CI], 95.2 to 97.6%), a sensitivity of 97.3% (95% CI, 96.4 to 98.0%), a specificity of 94.1% (95% CI, 91.0 to 96.4%), a positive predictive value of 98.2% (95% CI, 97.3 to 98.9%), a negative predictive value of 91.3% (95% CI, 88.3 to 93.4%), a positive likelihood ratio of 16.6 (95% CI, 10.8 to 26.9), and a negative likelihood ratio of 0.03 (95% CI, 0.02 to 0.04). Among patients with surgical confirmation of the diagnosis, misclassification, underestimation, and overestimation rates were 4.6%, 2.4%, and 2.2%, respectively, for the saliva miRNA signature and 27.2%, 15.1%, and 12.2%, respectively, for imaging (either transvaginal ultrasound, magnetic resonance imaging, or both).\nConclusions\nThis prospective, multicenter external validation study demonstrated the accurate performance of a saliva-based miRNA signature for the diagnosis of endometriosis in this cohort. (Funded by Ziwig; ClinicalTrials.gov number, NCT05244668.)\nNotes\nA data sharing statement provided by the authors is available with the full text of this article.\nSupported by unrestricted grants from Ziwig.\nDisclosure forms provided by the authors are available with the full text of this article.\nWe would like to extend our sincere thanks to Sophie Beranger, Lucie Bonin, Delphine Bouteiller, Patrice Crochet, Pierre Descargues, Nathalie Hoen, Zoe Husson, Ludmila Jornea, Alexandra Madar, Frédérique Perotte, Delphine Raffin, Salma Touleimat, Mélusine Turck, Eric Verspyck, and Emna Younsi for their contributions to this work.\nSupplementary Material\nInformation & Authors\nInformation\nPublished In\nNEJM Evidence\nCopyright\nCopyright © 2025 Massachusetts Medical Society.\nFor personal use only. Any commercial reuse of NEJM Group content requires permission.\nHistory\nPublished online: October 28, 2025\nPublished in issue: October 28, 2025\nTopics\nAuthors\nMetrics & Citations\nMetrics\nAltmetrics\nCitations\nExport citation\nSelect the format you want to export the citation of this publication.\nCited by\n- Changing the paradigm of endometriosis – from diagnosis to integrated long-term management: a joint society opinion paper, Reproductive BioMedicine Online, 53, 1, (105642), (2026).https://doi.org/10.1016/j.rbmo.2026.105642\n- Letter to the Editor: Clues to revising the conventional diagnostic algorithm for endometriosis, International Journal of Gynecology & Obstetrics, 173, 3, (1657-1658), (2026).https://doi.org/10.1002/ijgo.71051\n- Response: Clues to revising the conventional diagnostic algorithm for endometriosis, International Journal of Gynecology & Obstetrics, 173, 3, (1654-1656), (2026).https://doi.org/10.1002/ijgo.71050\n- Clinical Value of Circulating Endometrial Cells in the Diagnosis and Stratified Diagnosis of Endometriosis, Journal of Clinical Medicine, 15, 8, (3021), (2026).https://doi.org/10.3390/jcm15083021\n- SGLT2 Inhibitors and Mortality in Endometriosis With Type 2 Diabetes, JACC: Advances, (102681), (2026).https://doi.org/10.1016/j.jacadv.2026.102681\n- Menstrual Effluent in the Pathogenesis and Diagnosis of Endometriosis—A Systematic Review, Diagnostics, 16, 5, (677), (2026).https://doi.org/10.3390/diagnostics16050677\n- Non-Invasive Methods for Early Diagnosis of Endometriosis—A Comprehensive Narrative Literature Review, Healthcare, 13, 24, (3276), (2025).https://doi.org/10.3390/healthcare13243276\n- Urine and Serum miRNA Signatures for the Non-Invasive Diagnosis of Adenomyosis: A Machine Learning-Based Pilot Study, Diagnostics, 15, 23, (3012), (2025).https://doi.org/10.3390/diagnostics15233012\nLoading...","source_license":"CC0","license_restricted":false}