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

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Sun Yat-sen University

Status

Enrolling

Conditions

Ovarian Metastases of Colorectal Cancer

Treatments

Other: Prediction model

Study type

Observational

Funder types

Other

Identifiers

NCT06192030
wanghm7

Details and patient eligibility

About

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.

Full 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.

Enrollment

200 estimated patients

Sex

Female

Ages

18 to 85 years old

Volunteers

No Healthy Volunteers

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

Trial design

200 participants in 2 patient groups

Retrospective cohort
Description:
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.
Treatment:
Other: Prediction model
Prospective cohort
Description:
The same inclusion/exclusion criteria were applied for the same center prospectively. It is a validation cohort.
Treatment:
Other: Prediction model

Trial contacts and locations

1

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Central trial contact

Yuanxin Zhang, MD

Data sourced from clinicaltrials.gov

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