Using AI to predict risks in endometrial cancer management
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.
Regina Elena Cancer Institute · NCT06841653
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 type | Observational |
|---|---|
| Enrollment | 40 (estimated) |
| Ages | 18 Years and up |
| Sex | Female |
| Sponsor | Regina Elena Cancer Institute (other) |
| Locations | 1 site (Rome) |
| Trial ID | NCT06841653 on ClinicalTrials.gov |
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.
Who should consider this trial
Good fit: Ideal candidates include individuals over 18 years old with a histological diagnosis of endometrial hyperplasia or endometrioid adenocarcinoma undergoing total hysterectomy.
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.
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 performed: Other studies utilizing AI and multi-omics approaches have shown promise in improving cancer management, suggesting potential success for this novel approach.
Eligibility criteria
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 this trial is running
Rome
- IRCCS National Cancer Institute "Regina Elena" — Rome, Italy (RECRUITING)
Study contacts
- Study coordinator: Enrico Vizza, Doctor
- Email: enrico.vizza@ifo.it
- Phone: 06 52666974
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Endometrium Cancer, MultiOMics IMmune-IConographic pattern