Validation of a Saliva Micro–RNA Signature for Endometriosis

Sofiane Bendifallah, Horace Roman, Stéphane Suisse, Andrew Spiers, E. Petit, Erick Petit, Léa Delbos, Yohann Dabi, Cyril Touboul, T. Dennis Thomas, Thomas Dennis, Benjamin Merlot, Eric Sauvanet, Éric Sauvanet, Raffaèle Fauvet, R. Fauvet, Estelle Jamard, Hennetier Clotilde, Perrin Morgane, Benjamin Fedida, Krystel Nyangoh, Vincent Lavoué, Claire‐Marie Roger, Claire-Marie Roger, Nicolas Lucas, Thomas Darnaud, Anne-Sophie Boudy, Anne‐Sophie Boudy, Ludivine Genre, Pierre Lèguevaque, Pierre Leguevaque, Cherif Akldios, Mikhael Benjoar, Élodie Chantalat, Elodie Chantalat, Yann Tanguy Le Gac, Mathieu Poilblanc, Pascal Rousset, Hervé Fernandez, H. Fernandez, Francois Golfier, François Golfier, Philippe Descamps
NEJM evidence · 2025 · vol. 4(11) , pp. EVIDoa2400195 · doi:10.1056/evidoa2400195 · PMID:41147827 · W4415619543
article OA: closed CC0 ⤵ 2 in-corpus citations
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⚙ AI-generated summary by claude@2026-06, 2026-06-08 ⓘ

This study validated a saliva micro-RNA signature for endometriosis, showing high diagnostic accuracy, sensitivity, and specificity in a large, multicenter cohort.

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Abstract

BACKGROUND: Diagnosis 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. METHODS: The 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. RESULTS: The 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). CONCLUSIONS: This 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.).

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Condition tags

mesh:D004715endometriosis

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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