A.I and Machine Learning Based Risk Prediction Model to Improve the Clinical Management of
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 r
| Condition(s) | Endometrium Cancer |
|---|---|
| Status | Recruiting |
| Study type | Observational |
| 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. |
| Who can participate | 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; * Neoad |
| Ages | 18 Years |
| Sex | Female |
| Lead sponsor | Regina Elena Cancer Institute |
| Locations | Rome, Italy |
| Start date | 2024-06-20 |
| NCT ID | NCT06841653 |
| Official listing | https://clinicaltrials.gov/study/NCT06841653 |