Clinical trial · Observational
Predictors of Node Positivity in Endometrial Cancer
Histological and Molecular Characteristics Predict the Risk of Nodal Involvement in Endometrial Cancer: a Prospective Study
NCT05793333CI-TRIAL-00080874unknownClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
To investigate the role of histological and moleculr profile of endometrial cancer patietns in predicting the risk of nodal metastases in endometrila cancer patients.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Endometrial Cancer | Malignant Endometrial Neoplasm | CURATED_BROADER | 0.80 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- positive nodes
- timeFrame
- 12 months
- description
- positive nodes detected by sentinel node mappinig
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Written informed consent * Histologically confirmed endometrila cancer * Data on molecular genomic profiling (POLE mutated, p53 abnormalities, MMRd/MSI-H, and NSMP) * Data on histological characteristics of the ttumor * Execution of sentinel node mapping * Data on sentinel node status (negative vs. positive) Exclusion Criteria: * Stage IVB endoemtrial cancer * consent withdraw
References
Publications (1)
- DERIVEDBogani G, Lalli L, Casarin J, Ghezzi F, Chiappa V, Fanfani F, Scambia G, Raspagliesi F. Predicting the Risk of nOdal disease with histological and Molecular features in Endometrial cancer: the prospective PROME trial. Int J Gynecol Cancer. 2024 Sep 2;34(9):1366-1372. doi: 10.1136/ijgc-2024-005416. PMID 38658017