ML Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture

Chen Xiaoping

Status: Completed

Conditions: Peritoneal Metastasis

Treatments: Other: Peritoneal Metastasis

Study type: Observational

Funder types: Other

Identifiers

NCT06102278

PM-01

Details and patient eligibility

About

This study aimed to address the issue of peritoneal metastasis (PM) following the rupture of hepatocellular carcinoma (HCC) and its adverse impact on patient prognosis. Clinical data from 522 patients with ruptured HCC who underwent surgery at seven different medical centers were collected and analyzed. Machine learning models were employed for analysis and prediction.

Enrollment: 522 patients

Sex: All

Ages: 18 to 90 years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion criteria

Inclusion Criteria:(1) HCC confirmed by pathologists (2) two preoperative imaging findings suggestive of tumor rupture (3) R0 resection (4) first tumor detection -

Exclusion Criteria:(1) previous antitumor therapy (2) combination of other types of tumors (3) incomplete clinical data

Trial design

522 participants in 2 patient groups

Training cohort

Description:

All cases were randomly grouped according to 7:3, with 70% defined as the training group

Treatment:

Other: Peritoneal Metastasis

Validation cohort

Description:

All cases were randomly grouped according to 7:3, with 30% defined as the validation group

Treatment:

Other: Peritoneal Metastasis