ML Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture

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.

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Key information

Conditions

Peritoneal Metastasis

Age range

18 year–90 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Peritoneal Metastasis

Other

Patients experiencing postoperative peritoneal metastasis

Primary outcomes

overall survival

Time frame: 2018-2023

Overall survival (OS) was defined as the time from the date of surgery to death

Sponsors and collaborators

Lead sponsor

Chen Xiaoping

Other

Registry information

Official study title

Machine Learning Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture

Important dates

Study start: 2020
Primary completion: 2023
Study completion: 2023
First posted: Oct 26, 2023
Registry last updated: Oct 26, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed