Machine Learning Predicts Survival and Mutations in Ovarian Metastases of Colorectal Cancer

Machine Learning-based Model for Prediction of Survival and Mutations in Ovarian Metastases of Colorectal Cancer

The study aimed to develop and validate models to predict survival outcome and key mutations in patients with ovarian metastases of colorectal cancer, as well as to compare the differential gene expression between long-survival group and short-survival group.

Study Overview

• Status: Recruiting
• Conditions: Ovarian Metastases of Colorectal Cancer
• Intervention / Treatment: Other: Prediction model

Detailed Description

The investigator performed a retrospective-prospective cohort study with the aim of developing and validating comprehensive models to predict survival outcome and key mutations from multimodality data in patients with ovarian metastases of colorectal cancer. Secondly, the investigator aimed to compare the differential gene expression between long-survival group and short-survival group.

• Study Type: Observational
• Enrollment (Estimated): 200

Contacts and Locations

• Study Contact: Name: Yuanxin Zhang, MD; Phone Number: 8617372001179; Email: zyx163yxdz@163.com

Study Locations

• China
  • Guangdong
    • Guangzhou, Guangdong, China, 510655
      • Recruiting
      • Sixth Affiliated Hospital, Sun Yat-sen University
      • Contact: Huaiming Wang, MD; Email: wanghm7@mail.sysu.edu.cn
      • Principal Investigator: Huaiming Wang, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients with ovarian metastases from colorectal cancer

Description

Inclusion Criteria:

• Histologically confirmed colorectal cancer
• Unilateral or bilateral ovarian masses confirmed by peroperative imaging examination
• Patient requiring resection of their ovarian and/or peritoneal carcinomatosis
• 18 ≤ Age ≤ 85
• World Health Organization performance status ≤ 1
• Life expectancy > 12 weeks
• Adequate haematological, liver and renal function
• Patient information and signature of the informed consent form before the start of any treatment procedures

Exclusion Criteria:

• Ovarian metastases of origin other than colorectal
• Primary ovarian tumor
• Clinical data missing

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Retrospective cohort; The cohort was retrospectively enrolled in The Sixth Affiliated Hospital, Sun Yat-sen University from August 2010 to August 2022. It is a training cohort.	Other: Prediction model; We develop and validate clinical models to predict patient survival and gene signatures in ovarian metastases of colorectal cancer.
Prospective cohort; The same inclusion/exclusion criteria were applied for the same center prospectively. It is a validation cohort.	Other: Prediction model; We develop and validate clinical models to predict patient survival and gene signatures in ovarian metastases of colorectal cancer.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Overall survival	Overall survival was defined as the time from surgery to death, or to the last follow-up.	At least 3-year follow up
Disease-free survival	Disease-free survival was defined as the interval between surgery and the first peritoneal or distant relapse or death from any cause.	At least 1-year follow up
Peritoneal-free survival	Peritoneal-free survival was defined as the interval between surgery and the first peritoneal relapse. Ovarian metastasis has been shown to be a subtype of peritoneal metastasis.	At least 1-year follow up

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Rates of key gene mutation	Rates of key gene mutation, such as microsatellite instability-high/DNA mismatch repair	At least 1-year follow up

Collaborators and Investigators

• Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University

Study record dates

Study Major Dates

• Study Start (Actual): August 27, 2022
• Primary Completion (Estimated): August 1, 2025
• Study Completion (Estimated): August 1, 2025

Study Registration Dates

• First Submitted: October 9, 2023
• First Submitted That Met QC Criteria: January 4, 2024
• First Posted (Actual): January 5, 2024

Study Record Updates

• Last Update Posted (Actual): January 5, 2024
• Last Update Submitted That Met QC Criteria: January 4, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Keywords: Krukenberg tumor
• Additional Relevant MeSH Terms: Digestive System Diseases; Pathologic Processes; Neoplasms by Histologic Type; Neoplasms; Neoplasms by Site; Adenocarcinoma; Carcinoma; Neoplasms, Glandular and Epithelial; Gastrointestinal Neoplasms; Digestive System Neoplasms; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Neoplastic Processes; Neoplasms, Cystic, Mucinous, and Serous; Carcinoma, Signet Ring Cell; Colorectal Neoplasms; Neoplasm Metastasis; Krukenberg Tumor
• Other Study ID Numbers: wanghm7

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No