Clinical trial NCT03553589: Biomarkers for Diagnosis and Prognosis of Endometrial Carcinoma
Official title: Minimally and Non-invasive Methods for Early Detection and Progression of Endometrial Cancer
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Endometrial Cancer
Keywords: metabolomics
proteomics
early diagnosis
prognosis
Lead sponsor: Academisch Ziekenhuis Maastricht
Sponsor class: OTHER
Collaborators: name: University of Ljubljana, Faculty of Medicine
name: Medical University of Lublin
First posted: 2018-06-12
Enrollment: 400
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Women older than 18 years and able to sign the informed consent.

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.

Detailed description: Rationale: Endometrial cancer (EC) is the most frequent gynaecological malignancy in the developed world. Optimal treatment of EC depends on early diagnostics and pre-operative stratification to appropriately select the extent of surgery and to plan further therapeutic approach. Currently, invasive endometrial histology is the gold standard for diagnosis, as there are no valid non-invasive methods available, and patient stratification is based on histopathology and surgical findings. There is a great need for efficient and reliable screening test for asymptomatic women with high risk of EC including Lynch syndrome patients and tamoxifen treated patients. In addition, a prognostic test is needed to stratify pre-operatively EC patients with high risk of progression in need of radical surgery together with adjuvant chemo/ratio therapy from EC patients with good prognosis. In this project the investigators are addressing this lack of non-invasive diagnostic and prognostic biomarkers of EC.

Objective: the investigators aim to identify diagnostic serum metabolite and protein biomarker signatures for early detection of cancer in asymptomatic high-risk population and (secondary objective) prognostic biomarkers for selection of patients with poor prognosis.

Eligibility criteria: Inclusion Criteria Cases:

* endometrioid, serous, clear cell or mucinous endometrial cancer
* dedifferentiated endometrial cancer
* high grade or low grade endometrial cancer

Inclusion Criteria Controls:

* benign uterine diseases, e.g. myoma uteri, prolapsed uterus
* prophylactic hysterectomy for Lynch syndrome

Exclusion Criteria Cases:

* atypical hyperplasia
* other types of cancer
* sarcoma uteri
* previous diagnosis of endometrial cancer

Exclusion Criteria Controls:

* any cancer
* benign ovarian diseases
* previous EC
* pregnancy at the time of enrollment

Primary outcomes:
measure: Creation of a diagnostic algorithm
timeFrame: 2020-2021
Secondary outcomes:
measure: Creation of a prognostic algorithm
timeFrame: 2021
Other outcomes:
Locations:
city: Maastricht
country: Netherlands
facility: Maastricht University Medical Centre
city: Veldhoven
country: Netherlands
facility: Maxima Medical Centre
city: Lublin
country: Poland
facility: Lublin Medical University
city: Ljubljana
country: Slovenia
facility: Faculty of Medicine, University of Ljubljana
city: Ljubljana
country: Slovenia
facility: University Medical Centre, Ljubljana
Study officials:
affiliation: Maastricht University Medical Centre
name: Andrea Romano
role: PRINCIPAL_INVESTIGATOR
affiliation: Faculty of Medicine, University of Ljubljana, Slovenia
name: Tea Lanišnik Rižner, Prof. Dr.
role: STUDY_CHAIR
References: