Clinical trial · Interventional
Predicting Outcome of Cytoreduction in Advanced Ovarian Cancer
Predicting Outcome of Cytoreduction in Advanced Ovarian Cancer, Using a Machine Learning Algorithm and Patterns of Disease Distribution at Laparoscopy (PREDAtOOR)
NCT06017557CI-TRIAL-00099335PREDAtOORrecruitingN/AClinicalTrials.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)
PREDAtOOR is a pilot study and this study aims at improving the selection of the best treatment strategy for patients with advanced ovarian cancer by using Camera Vision (CV) to predict outcomes of cyto reduction at the time of Diagnostic laparoscopy.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Ovarian Cancer Stage III | Malignant Ovarian Neoplasm | CURATED_BROADER | 0.78 |
| Ovarian Cancer Stage IV | Malignant Ovarian Neoplasm | CURATED_BROADER | 0.78 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Artificial Intelligence | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- Clinical Stage III-IV Ovarian Cancer
- description
- individuals who have been diagnosed or are suspected to have Clinical Stage III-IV Ovarian Cancer and CT and MRI have most commonly been used to identify sites and amounts of tumors in the abdomen and can help determine if these tumors can be safely removed by surgery. However, these imaging methods are only a prediction, and sometimes a diagnostic laparoscopy (putting a camera in the abdomen to look at all sites of disease) is performed to help this decision process.
- interventionNames
- Diagnostic Test: Artificial Intelligence
Primary outcomes (2)
- measure
- a) Number of Participants with Treatment Diagnostic Laparoscopy assessed by Predictive Index Value.
- timeFrame
- through study completion, an average of 1 year
- description
- The Fagotti score, also known as the Predictive Index Value (PIV), is determined through the evaluation of six abdominal areas during laparoscopic exploration. These areas include the parietal peritoneum, diaphragm, greater omentum, bowel, stomach/spleen/lesser omentum, and liver. A score of 2 is assigned to each area with visible tumor spread, allowing for a maximum score of 14. Notably, a PIV score of 10 or higher signifies a threshold for triaging patients toward neoadjuvant chemotherapy. To create a predictive model for cytoreduction outcomes during diagnostic laparoscopy, advanced deep neural networks will be trained. This aims to automate PIV score assessment using a fully supervised approach and deduce features from images obtained during diagnostic laparoscopy to predict the possibility of a resection target above 1 cm or a lack of indication for cytoreductive surgery in a weekly supervised manner.
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Patients treated at Fondazione Policlinico Gemelli Hospital, Rome Italy, Trillium -Credit Valley Hospital, Mississauga, Ontario and Princess Margaret Cancer Centre, Toronto, Canada * Patients fit for cytoreductive surgery * Patients with a primary diagnosis of suspect Stage III-IV ovarian cancer * Patients selected for interval cytoreductive surgery after NACT Exclusion Criteria: * Patients with pre-operative Stage I-II disease confined to the pelvis * Patients unfit for surgery * Lack of information about patients' surgical outcomes and clinicopathological characteristics * LGSOC, Clear cell and mucinous, non-epithelial histologic subtypes (if available)
References
Publications (0)
Data not yet available
No reference posted for this study.