Multicenter Validation of the Salivary miRNA Signature of Endometriosis

Study Overview
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Brief Summary
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ENDOmiARN Salive Test is a multicentre external validation study of a salivary signature of endometriosis carried out in France in Obstetrics and Reproductive Medicine departments, in order to evaluate its performance and discuss its use in clinical practice. The clinical application is to significantly reduce the time to diagnosis and improve the care pathway for endometriosis. The study population is made up of women aged 18 to 43 years with formally diagnosed endometriosis or suspected endometriosis who are already receiving either medical (MAP) or surgical treatment as part of their routine care. The patients concerned by the study are managed without any change in the care pathway, nor any change in the therapeutic indications, nor any change in the diagnostic examinations (imaging or biology) required according to the context, which are carried out in accordance with the HAS recommendations. In this study, the management and follow-up of patients : Are not imposed by the study: the doctor remains free to make medical prescriptions (treatments and examinations) and to determine the interval between consultation visits, Are not modified in comparison with the usual follow-up, except for the performance of : Collection of saliva Electronic collection of the answers to the questionnaires completed by the patient

Official Title
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Multicenter Validation of the Salivary miRNA Signature of Endometriosis - The ENDOmiARN Salive Test Study

Conditions
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Endometriosis

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Patient aged between 18 and 43 years, Patient having dated and signed the consent form, Patient affiliated to the French health system, Patient with pelvic MRI and/or pelvic ultrasound, Patient from one of the 3 study populations: Patient with a formal endometriosis diagnosed by clinical examination and imaging AND an indication for specialised endometriosis follow-up or medically assisted procreation (MAP) or surgery validated by RCP (in routine care); Patient with suspected endometriosis for whom the diagnosis is the source of a discrepancy between clinical and radiological data AND a surgical indication validated by RCP (in routine care); Patient with a gynaecological indication for surgery of the small pelvis by laparoscopy or laparoscopy validated in RCP (in routine care) AND symptoms suggestive of endometriosis (dysmenorrhoea, ....)(1). Exclusion Criteria: Patient with recurrence of deep endometriosis (excluding endometrioma), Patient with endometriosis of the torus and/or utero-sacral ligaments without indication for surgery, Patient with parietal endometriosis alone without indication for surgery, Patient with adenomyosis alone on imaging without indication for surgery, Patient with gynaecological infection requiring surgical management, Pregnant patient, Patient infected with the human immunodeficiency virus (HIV), Patient with significant difficulties in reading or writing the French language, Patient with a personal history of cancer, Patient unable to comply with study and/or follow-up procedures, Patient who has objected to the collection of her data. Patient participating in another clinical research study.

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 43 Years

Sexes Eligible for Study
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Female

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| At least a 90% Sensitivity (True Positive Rate) of Endometriosis diagnotic confirmation using a miRNA signature | External validation of the salivary signature of endometriosis miRNAs | Through the end of study inclusions, an average of 1 year | 
| At least a 90% Specificity (True Negative Rate) of Endometriosis diagnotic confirmation using a miRNA signature | External validation of the salivary signature of endometriosis miRNAs | Through the end of study inclusions, an average of 1 year | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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miRNA, MAP, machine learning algorithms