Development and Validation of a PSN-AI Prediction Model

Sixth Affiliated Hospital, Sun Yat-sen University50 enrolled

Overview

Heterogeneity concerning survival in synchronous peritoneal metastasis from patients with colorectal cancer exists, thereby further classification is urgently required. This study aimed to validate a PSN-AI model based on DNA ploidy, stroma-tumor fraction, and nucleotyping (PSN) for the prediction of survival of synchronous peritoneal metastasis from colorectal cancer.

Study Type

OBSERVATIONAL

Enrollment

Conditions

Colorectal Cancer Peritoneal Metastases

Interventions

Analyse pathologic slidesOTHER

HE-stained whole slide images were used for the validation of the PSN-AI model.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 80 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Histological proof of synchronous peritoneal metastases of a nonappendiceal colorectal adenocarcinoma. * Resectable disease determined by computed tomography (CT) and a peritoneal cancer index (PCI) of ≤20 at diagnostic laparoscopy or laparotomy; * No evidence of systemic (e.g. liver, lung) colorectal metastases within three months prior to enrolment; * Undergoing cytoreduction surgery for synchronous peritoneal metastasis from colorectal cancer. Exclusion Criteria: * Combined with other types of malignant tumors.

Locations (1)

Sixth Affiliated Hospital, Sun Yat-sen University

Guangzhou, Guangdong, China

RECRUITING

Outcomes

Primary Outcomes

Overall survival

The time between the date of diagnosis and the date of death (due to any cause) or the date of last follow-up.

Time frame: At least 1-year follow up

Secondary Outcomes

Progression-free survival

The time from diagnosis to the onset of disease progression.

Time frame: At least 1-year follow up

Central Contacts

Qiyuan Qin, PhD

CONTACT

+86-20-38254052 qinqy3@mail.sysu.edu.cn

Data from ClinicalTrials.gov

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