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.

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.

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