Our publications
Our work is published in international peer-reviewed scientific journals. They underpin all the discovery, development and validation phases of our tests. As these publications have appeared in international journals in English, we are making them available in their original language.
Validation of the Salivary miRNA Signature of Endometriosis — Interim Data
Bendifallah S., Dabi Y., Suisse S., et al. I June 2023
The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early and noninvasive diagnosis of the disease. The 109-miRNA saliva signature is the product of miRNA bio- markers and AI modeling. We designed a multicenter study to provide external validation of its diagnostic accuracy. We present here an interim analysis.
Saliva microRNA signature to diagnose endometriosis: A cost-effectiveness evaluation of the Endotest®
Ferrier C., Bendifallah S., Suisse S., Dabi Y., Touboul C., Puchar A., Zarca K. and Durand Zaleski I November 2022
Objective: To evaluate a saliva diagnostic test (Endotest®) for endometriosis compared with the conventional algorithm. Design: A cost-effectiveness analysis with a decision-tree model based on literature data. Setting: France. Population: Women with chronic pelvic pain.
Endometriosis-associated infertility diagnosis based on saliva microRNA signatures
Dabi Y., Suisse S., Puchar A., Delbos L., Poilblanc M., Descamps P., Haury J., Golfier F., Jornea L., Bouteiller D., Touboul C. and Bendifallah S. I October 2022
Research question: Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome? Design: The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis.
MicroRNome analysis generates a blood-based signature for endometriosis
Bendifallah S., Suisse S., Dabi Y., et al. I March 2022
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),…
Machine learning algorithms as new screening approach for patients with endometriosis
Bendifallah S., Suisse S., Puchar A., et al. I January 2022
Endometriosis—a systemic and chronic condition occurring in women of childbearing age—is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as screening and triage tests for endometriosis to replace diagnostic laparoscopy, none have been implemented routinely in clinical practice.
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