A.I and Machine Learning Based Risk Prediction Model to Improve the Clinical Management of Endometrial Cancer.
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
40 participants
Jun 20, 2024
OBSERVATIONAL
Conditions
Summary
Prediction of preoperative endometrial biopsy: the evolution from hyperplasia to cancer, the prognosis and the risk of recurrence. Intelligence methods artificial risk will be used to redefine the current risk classes including our profile immuno-mutational to provide a more precise characterization and closer to the real prognosis of the patient.
Eligibility
Inclusion Criteria3
- 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 Criteria6
- 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.
Locations(1)
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NCT06841653