Satisfactory Debulking Prediction Model for Advanced Ovarian Cancer Based on PET-CT Image Data

July 30, 2024 updated by: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Satisfactory Debulking Prediction Model for Advanced Ovarian Cancer Based on PET-CT Image Data and Its Clinical Application

This project intends to conduct a multicenter retrospective study to evaluate the satisfactory reduction of advanced ovarian cancer using PET-CT images, and explore the correlation between molecular biological characteristics and clinical characteristics of ovarian cancer through high-throughput sequencing genomics combined with radiomics.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Ovarian cancer is the gynecological malignant tumor with the highest fatality rate. More than 70% of patients are diagnosed with advanced stage, often involving various organs of the pelvis and abdomen, which increases the difficulty of surgical resection, and the 5-year survival rate is only 30%. Surgical treatment is the cornerstone of the treatment of ovarian cancer, and whether it can achieve satisfactory tumor reduction is an important factor affecting the prognosis of ovarian cancer. At present, the methods used to evaluate whether satisfactory tumor reduction can be achieved include Suidan score based on CT image and Fagotti score based on laparoscopic exploration, but there are problems such as low sensitivity, poor specificity or strong subjectivity, and the efficiency of predicting satisfactory tumor reduction is only about 60%. In recent years, PET-CT has been widely used in tumor diagnosis. Pet-ct combined with PET metabolic imaging technology and traditional CT scanning can help to distinguish the nature of tumors, assess the systemic tumor load, define the scope of the lesion, and provide the metabolic status of various parts of the body. The application value of PET-CT related imaging features and metabolic information in ovarian cancer needs to be clarified. Our team's previous study found that PET-CT related images and metabolic information showed certain advantages in predicting satisfactory resection of ovarian cancer, and the AUC reached 0.85, which was better than the current CT image score and laparoscopic score. Therefore, this project intends to conduct a multicenter retrospective study to evaluate the satisfactory tumor reduction rate of advanced ovarian cancer using PET-CT images to guide clinical practice and predict the prognosis of patients. At the same time, we will explore the molecular biological characteristics and clinical relevance of ovarian cancer through the combination of high-throughput sequencing genomics and radiomics.

Study Type

Observational

Enrollment (Estimated)

146

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 520120
        • Recruiting
        • The Sun Yat-sen Memorial Hospital of Sun Yat-sen University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

A total of 96 patients with advanced ovarian cancer who underwent PET-CT examination before the surgery, and received primary debulking surgery at our center from July 2017 to April 2024 were included for model development. Additionally, 50 patients from Zhejiang Cancer Hospital were included for model validation.

Description

Inclusion Criteria:

  • Pathological type is epithelial ovarian cancer.
  • Underwent primary debulking surgery at our hospital.
  • Postoperative pathological staging is FIGO stage IIB or above.
  • Clinical, surgical, and pathological data of the patient are mostly complete.

Exclusion Criteria:

  • Pathological type is non-epithelial ovarian cancer.
  • Underwent fertility-preserving surgery or palliative surgery.
  • Presence of infection during PET/CT image acquisition.
  • Concurrent other malignant tumors.
  • Severe diseases of other major organs.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
SYSU cohort
Patients cohort from Sun Yat-sen Memorial Hospital, as the training cohort.
Diagnostic test: Radio-score
A score based on the LASSO regression model predicting the R0 resection of the primary debulking surgery of advanced ovarian cancer.
ZJCH cohort
Patients cohort from Zhejiang Cancer Hospital, as the external validation cohort.
Diagnostic test: Radio-score
A score based on the LASSO regression model predicting the R0 resection of the primary debulking surgery of advanced ovarian cancer.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
R0 resection
Time Frame: yes or not
In patients with advanced ovarian cancer, the residual status after initial cytoreductive surgery is defined as follows: complete resection is defined as R0 resection, whereas visible residual tumor lesions during surgery are defined as non-R0 resection
yes or not

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
5-year progression-free survival (PFS)
Time Frame: 5 years
PFS was calculated from the date of the last chemotherapy until disease progression or death due to any cause.
5 years
5-year overall survival (OS)
Time Frame: 5-year
OS was calculated from the date of the primary debulking surgery until death due to any cause.
5-year
Response to platinum-based chemotherapy
Time Frame: At least 6 months after the last chemotherapy
After the last chemotherapy, treatment efficacy was assessed according to NCCN guidelines. For primary tumor, patients who relapsed 6 months or more after initial chemotherapy were termed platinum-sensitive. In contrast, patients whose disease recurred in less than 6 months were classified as platinum-resistant.
At least 6 months after the last chemotherapy

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Investigators

  • Principal Investigator: huaiwu Lu, The Sun Yat-sen Memorial Hospital of Sun Yat-sen University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 1, 2024

Primary Completion (Estimated)

May 31, 2026

Study Completion (Estimated)

May 31, 2026

Study Registration Dates

First Submitted

July 30, 2024

First Submitted That Met QC Criteria

July 30, 2024

First Posted (Actual)

August 1, 2024

Study Record Updates

Last Update Posted (Actual)

August 1, 2024

Last Update Submitted That Met QC Criteria

July 30, 2024

Last Verified

July 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • SYSKY-2024-503-01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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