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NCT Number: NCT06268626

Detection of Endometrial Cancer Through Risk Modelling

The study goal is to investigate a non-invasive approach to predict endometrial cancer (EC) risk, better understand disease progression and identify opportunities for intervention.

This two-part case-cohort prospective study will recruit patients whose abnormal uterine bleeding is being evaluated via endometrial biopsy. Participants will complete an online health questionnaire, and a subset will be invited to self-collect vaginal samples for sequencing.

Selected sequenced participants will be invited for longitudinal monitoring (questionnaires, wearable fitness tracker) and an additional vaginal self-collection to identify persistent genetic mutations or microbiome alterations 6-8 months later.

Recruiting

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Key information

Age range

40 year and older

Sex eligibility

Female

Study type

Observational

Primary location

About this study

Purpose:

To improve the prediction of EC and its precursors by integrating data from questionnaires and biological biomarkers obtained from non-invasive tests (vaginal DNA and microbiome swabs, vaginal pH). We also want to better understand pre-malignant disease progression and identify opportunities for earlier intervention.

Hypotheses:

  • Risk factors in combination with ultrasound data, and patterns of abnormal bleeding are associated with endometrial cancer and its precursors.
  • Prediction of pathology is improved by including mutation and microbiome data from noninvasive tests combined with traditional risk factors.
  • Persistence of mutations and microbiome alterations is more common in patients with endometrial hyperplasia than other benign diagnoses and is associated with lifestyle factors.

Justification:

Non-invasive tests and questionnaires may be used to predict onset of endometrial carcinoma or its precursors and can be used to triage those participants with abnormal bleeding who require an endometrial biopsy.

Objectives:

To enhance understanding of the progression of EC and propose non-invasive methods for detection in patients who are experiencing abnormal uterine bleeding and have already been referred to a gynecologist for an endometrial biopsy.

Research Design:

This is a prospective case-cohort study that will recruit n=1000+ participants over the age of 35 years whose abnormal uterine bleeding is being evaluated via endometrial biopsy. Prospective participants will consent to access the information in their medical records, including access to their pathology report. A subset of participants (n=450) will be invited to self-collect vaginal DNA and microbiome samples using swabs and vaginal pH using a litmus kit for sequencing and analysis. A subset of those who retain their uterus (i.e. are not directed to a hysterectomy per standard clinical management) (n=200+), will be invited to take part in longitudinal monitoring using a wearable fitness tracker (Fitbit) and questionnaires, and an additional vaginal self-collection.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Study Part A:

  • 40 years and older
  • Experiencing unexplained abnormal uterine bleeding (i.e., not from IUD, etc.)
  • Have an intact uterus
  • Referred for an endometrial biopsy

Study Part B/Longitudinal monitoring:

  • Those selected for sequencing (from Part A) and who retained their uterus.

Exclusion criteria

Study Part A:

  • Endometrial sampling, pelvic radiation, or vaginal infection (vaginosis, yeast) in the past 3 months
  • Started hormone therapy (HRT, birth control, IUD) in the past year (with the exception of tamoxifen)
  • Intercourse, vaginal product use, or douching in the past 48 hours

Study Part B/Longitudinal monitoring:

  • Same as Study Part A
  • EC or EIN, or anyone who is recommended a hysterectomy

Treatment and study plan

Primary outcomes

  1. Diagnostic Performance of cfDNA Mutation Detection for Endometrial Pathology

    Time frame: Through study completion, anticipated 1-2 years

    Cell-free DNA (cfDNA) extracted from vaginal swabs will be sequenced to identify endometrial cancer-associated mutations. Diagnostic performance will be evaluated by calculating sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for detecting endometrial pathology, using biopsy-confirmed pathology as the reference standard.

  2. Association Between Vaginal Microbiome Profile and Endometrial Pathology

    Time frame: Through study completion, anticipated 1-2 years

    Vaginal microbiome DNA extracted from swabs will be sequenced and processed into operational taxonomic units (OTUs) using an in-house bioinformatics pipeline. OTUs will be compared across biopsy-confirmed pathology groups and evaluated against previously published microbiome signatures predictive of endometrial cancer.

Study contacts

Contact information is provided by the study sponsor or research team.

Aline Talhouk, PhD

CONTACT

[email protected]

+1 (604) 875-4111 ext. 21365

Jennifer Ellis-White

CONTACT

[email protected]

+1 (604) 875-4111 ext. 21369

Sponsors and collaborators

Lead sponsor

University of British Columbia

Other

Collaborators

  • Canadian Institutes of Health Research (CIHR)

Registry information

Official study title

Non-Invasive Strategies for Early Detection of Uterine Cancer in Patients With Abnormal Uterine Bleeding

Acronym: DETECTR

Important dates

Study start
2024
Primary completion
2027
Study completion
2027
First posted
Feb 20, 2024
Registry last updated
Apr 16, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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