Biomarkers for Diagnosis and Prognosis of Endometrial Carcinoma
BioEndoCar
Minimally and Non-invasive Methods for Early Detection and Progression of Endometrial Cancer
1 other identifier
observational
400
3 countries
5
Brief Summary
Endometrial cancer (EC) is the most frequent gynecological malignancy but there is currently lack of both non-invasive diagnostic tools and novel markers to stratify patients based on their risk of future recurrence. Patient care could be improved by advances in these two aspects. In the present study, the investigators aim to identify diagnostic serum metabolite and protein biomarker signatures for early detection of cancer in asymptomatic high-risk population and prognostic biomarkers for selection of patients with poor prognosis.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Oct 2018
Typical duration for all trials
5 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 30, 2018
CompletedFirst Posted
Study publicly available on registry
June 12, 2018
CompletedStudy Start
First participant enrolled
October 1, 2018
CompletedPrimary Completion
Last participant's last visit for primary outcome
June 1, 2021
CompletedStudy Completion
Last participant's last visit for all outcomes
June 1, 2021
CompletedDecember 5, 2018
December 1, 2018
2.7 years
May 30, 2018
December 3, 2018
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Creation of a diagnostic algorithm
Blood metabolome and proteome will be analysed and bioinformatics/biostatistical analysis will be used to derive diagnostic algorithms based on blood metabolites, proteins and clinical data. Algorithms in the biomarker discovery study will be developed by comparing EC and patients with benign uterine pathologies.
2020-2021
Secondary Outcomes (1)
Creation of a prognostic algorithm
2021
Study Arms (2)
Cases
Women older than 18 years and diagnosed with endometrial cancer will be included. Blood sampling will be performed on all subjects and will be used for proteomics and metabolomics analyses.
controls
Women older than 18 years and with a benign endometrial disturbance will be included. Blood sampling will be performed on all subjects and will be used for proteomics and metabolomics analyses.
Interventions
Blood sampling (10 mL) prior to standard care (e.g. surgery, medical treatment)
Eligibility Criteria
Women older than 18 years and able to sign the informed consent.
You may qualify if:
- endometrioid, serous, clear cell or mucinous endometrial cancer
- dedifferentiated endometrial cancer
- high grade or low grade endometrial cancer
- benign uterine diseases, e.g. myoma uteri, prolapsed uterus
- prophylactic hysterectomy for Lynch syndrome
You may not qualify if:
- atypical hyperplasia
- other types of cancer
- sarcoma uteri
- previous diagnosis of endometrial cancer
- any cancer
- benign ovarian diseases
- previous EC
- pregnancy at the time of enrollment
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Andrea Romanolead
- University of Ljubljana, Faculty of Medicinecollaborator
- Medical University of Lublincollaborator
Study Sites (5)
Maastricht University Medical Centre
Maastricht, Netherlands
Maxima Medical Centre
Veldhoven, Netherlands
Lublin Medical University
Lublin, Poland
Faculty of Medicine, University of Ljubljana
Ljubljana, Slovenia
University Medical Centre, Ljubljana
Ljubljana, Slovenia
Related Links
Biospecimen
serum samples
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Andrea Romano
Maastricht University Medical Centre
- STUDY CHAIR
Tea Lanišnik Rižner, Prof. Dr.
Faculty of Medicine, University of Ljubljana, Slovenia
Central Study Contacts
Roy Kruitwagen, Prof. Dr.
CONTACT
Study Design
- Study Type
- observational
- Observational Model
- CASE CONTROL
- Time Perspective
- CROSS SECTIONAL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR INVESTIGATOR
- PI Title
- PhD. Assistant Professor
Study Record Dates
First Submitted
May 30, 2018
First Posted
June 12, 2018
Study Start
October 1, 2018
Primary Completion
June 1, 2021
Study Completion
June 1, 2021
Last Updated
December 5, 2018
Record last verified: 2018-12