[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"trial:NCT06907303":3,"trial-entities:NCT06907303":84,"trial-summary:NCT06907303":25},{"id":4,"nct_id":4,"org_study_id":5,"brief_title":6,"official_title":7,"overall_status":8,"completion_date":9,"status_verified_date":10,"last_update_date":11,"start_date":12,"sponsor_name":13,"lead_sponsor_class":14,"has_dmc":15,"brief_summary":16,"detailed_description":17,"conditions":18,"keywords":20,"study_type":24,"primary_purpose":25,"phases":26,"enrollment_info":27,"interventions":30,"primary_outcomes":37,"secondary_outcomes":42,"sex":47,"minimum_age":48,"maximum_age":49,"healthy_volunteers":25,"eligibility_criteria":50,"std_ages":61,"locations":63,"central_contacts":80,"overall_officials":81,"references":82,"see_also_links":83},"NCT06907303","WrenEndoMstudy 01","RNA Assays for Endometriosis Detection and Diagnosis","Development and Evaluation of RNA-based Markers for Detecting and Diagnosing Endometriosis","ENROLLING_BY_INVITATION","2026-12-31","2025-03","2025-04-02","2024-01-01","Wren Laboratories LLC","INDUSTRY",false,"Endometriosis is a common disease that affects up to 10% of women of reproductive age. Diagnosis, however, is typically delayed (up to 12 years) and is usually made after surgery. A key unmet need therefore is an accurate biomarker that can be used to detect the disease early. This study is a prospective trial to identify candidate mRNA-markers which can be used to aid in the diagnosis of this disease. It is a discovery\u002Fvalidation study that will identify and confirm a gene expression panel that is specific for endometriosis and provides a non-invasive tool for future use.","Endometriosis is a common disease that affects up to 10% of women of reproductive age. Diagnosis, however, is typically delayed (up to 12 years) and is typically made after surgery. A key unmet need therefore is an accurate, non-invasive biomarker that can be used to detect the disease early.\n\nWe hypothesize that endometriosis-related circulating gene expression can be identified using transcriptomic and bioinformatics approaches and used to construct an accurate diagnostic tool for this condition.\n\nThe primary objective is to develop a gene signature that detects endometriosis. The hypothesis is that this disease is characterized by a set of genes that characterize endometriosis tumor biology.\n\nThe aim is to detect over-expressed genes (elevated mRNA expression) in endometriosis tissue. The goal is to identify 10-25 biomarker genes that are highly expressed to form a candidate biomarker panel.\n\nHighly expressed genes will be determined against samples collected from age\u002Fmenstrual stage matched controls. A bio-informatics approach will be used to identify these over-expressed genes. This form the basis of a potential diagnostic panel.\n\nPer PICOT criteria:\n\n* The target patient population are women aged 20-35 years with a pathological diagnosis of endometriosis.\n* The intervention is sample collection at the time of diagnosis (tissue, blood, saliva)\n* The comparison group are normo-ovulatory subjects (age 20-25 years) undergoing surgery for benign cervical lesions.\n* The outcome is a gene signature that is associated with endometriosis.\n* The follow-up time is one year.\n\nThe secondary objective is to test the diagnostic utility of the 10-25 gene panel. This will be undertaken using the retrospectively collected samples.\n\n* Each of the highly expressed genes will be measured and quantified using an RT-PCR approach.\n* Genes that are statistically over-expressed in the endometriosis samples will be selected for a PCR panel.\n* The expression of genes in the PCR panel will be scored.\n* Low scores will be related to \"control\" and higher scores to \"endometriosis\".\n* The scores will be formally evaluated as a diagnostic (area under the curve analysis, accuracy, sensitivity and specificity metrics).\n* A specific comparison will be made between the endometriosis cohort and the control cohort.\n* The metrics for a successful assay are:\n\n  * Accuracy \\>80%\n  * Sensitivity \\>90%\n  * Specificity \\>85%\n  * AUC \\>0.8",[19],"Endometriosis",[19,21,22,23],"Diagnosis","Gene Expression","PCR","OBSERVATIONAL",null,[],{"count":28,"type":29},400,"ESTIMATED",[31],{"type":32,"name":33,"description":34,"armGroupLabels":35},"DIAGNOSTIC_TEST","EndoDx","PCR assay for Endometriosis diagnosis",[36,19],"Control",[38],{"measure":39,"description":40,"timeFrame":41},"Develop a gene signature that detects endometriosis","Gene expression levels in samples from endometriosis subjects and controls","12-18 months",[43],{"measure":44,"description":45,"timeFrame":46},"Assess the diagnostic utility of the gene signature to differentiate between endometriosis and controls","Algorithmic analysed normalized gene expression levels in samples from endometriosis subjects and controls","6 months","FEMALE","20 Years","35 Years",{"inclusion":51,"exclusion":55,"raw_text":60},[52,53,54],"a history of infertility more than 1 year","age 20-35 years","normal liver and kidney function, without gynaecological and other systemic disease",[56,57,58,59],"polycystic ovary syndrome, hyperprolactinemia","severe cardiovascular system, liver, kidney, and hematopoietic system disease","autoimmune disease","uterine fibroids, endometritis, non-vegetative ovarian cysts, ovarian malignancies, and internal genital tuberculosis","Inclusion Criteria:\n\nFor the endometriosis cohort\n\n* a history of infertility more than 1 year\n* age 20-35 years\n* normal liver and kidney function, without gynaecological and other systemic disease\n\nInclusion criteria for controls include normo-ovulatory history, aged between 20-35 years, who exhibit normal liver and kidney function, and do not have any systemic diseases including autoimmune disease.\n\n\\-\n\nExclusion Criteria:\n\nFor the endometriosis cohort\n\n* polycystic ovary syndrome, hyperprolactinemia\n* severe cardiovascular system, liver, kidney, and hematopoietic system disease\n* autoimmune disease\n* uterine fibroids, endometritis, non-vegetative ovarian cysts, ovarian malignancies, and internal genital tuberculosis\n\nExclusion criteria for the controls includes gynaecological malignancies and genital tuberculosis.\n\n\\-",[62],"ADULT",[64,73],{"facility":65,"city":66,"state":67,"zip":68,"country":69,"geoPoint":70},"Wren Laboratories","Branford","Connecticut","06405","United States",{"lat":71,"lon":72},41.27954,-72.8151,{"facility":74,"city":75,"country":76,"geoPoint":77},"University of Cape Town","Cape Town","South Africa",{"lat":78,"lon":79},-33.92584,18.42322,[],[],[],[],{"nct_id":4,"conditions":85,"biomarkers":86},[19],[]]