Clinical trial Recruiting at 1 site Observational Ages 18 and up Women only

Using AI to predict risks in endometrial cancer management

Official title: A.I and Machine Learning Based Risk Prediction Model to Improve the Clinical Management of Endometrial Cancer: a Composite Approach Integrating the MultiOMics IMmune-IConographic Pattern (MOMIMIC Score) Towards Precision Oncology and Surgery.

Run by Regina Elena Cancer Institute · NCT06841653 · Data updated 2026-11-12

This study is testing if using artificial intelligence can help doctors better predict risks and improve treatment for women with endometrial cancer, especially to help preserve fertility in those with low-risk profiles.

Quick facts

Study typeObservational
Ages18 Years and up
SexWomen only
Enrollment40 (estimated)
SponsorRegina Elena Cancer Institute
Academic / other
Locations1 site (Rome)
StatusRecruiting
StartedJune 20, 2024
Main results expectedJune 20, 2026
Study endsJune 20, 2026
Registry record updatedFebruary 24, 2025
Trial IDNCT06841653 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Ideal candidates include individuals over 18 years old with a histological diagnosis of endometrial hyperplasia or endometrioid adenocarcinoma undergoing total hysterectomy.

Probably not a fit

Patients with uncontrolled comorbidities, infections of the endometrial cavity, synchronous cancers, or those who have undergone neoadjuvant treatments may not benefit from this study.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study aims to identify new risk factors for endometrial cancer by employing an integrated multi-omics approach linked to a specific immune pattern known as the MOMIMIC score. It focuses on predicting the progression from precancerous lesions to endometrial carcinoma, assessing prognosis and recurrence risks to aid clinical decision-making. The study utilizes artificial intelligence algorithms to enhance the precision of hysteroscopic procedures and improve the characterization of patients' prognoses. By modulating surgical approaches based on risk profiles, the study seeks to preserve fertility in young patients with low-risk profiles.

Why it matters

Potential benefit: If successful, this approach could lead to more accurate risk assessments and tailored treatments for patients with endometrial cancer.

How similar studies have gone: Other studies utilizing AI and multi-omics approaches have shown promise in improving cancer management, suggesting potential success for this novel approach.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* Age \> 18 years;
* Histological diagnosis of endometrial hyperplasia, endometrioid adenocarcinoma of the endometrium, healthy endometrium in patients undergoing total hysterectomy for benign extra-endometrial disease;
* Written informed consent (to the study and data processing), for the party's patients only prospective and/or in follow-up) For the retrospective cohort: availability of samples adequately stored at the biobank of the Institute and availability of data relating to follow-up (at least 2 years)

Exclusion Criteria:

All exclusion criteria adopted in the surgical protocols will be applied to the study. In particular:

* Comorbidities not controlled with adequate medical therapy;
* Infections of the endometrial cavity (pyometra);
* Synchronous cancer;
* Neoadjuvant treatments;
* Previous radiotherapy treatments of the pelvic region;
* Hormone therapies.

Where it's running

  • IRCCS National Cancer Institute "Regina Elena"
    Rome, Italy
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.