ML Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture

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

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06102278

Enrollment

522

Registered

2023-10-26

Start date

2020-01-01

Completion date

2023-04-01

Last updated

2023-10-26

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Peritoneal Metastasis

Brief summary

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.

Interventions

OTHERPeritoneal Metastasis

Patients experiencing postoperative peritoneal metastasis

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to 90 Years

Healthy volunteers

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 \-

Design outcomes

Primary

Measure	Time frame	Description
overall survival	2018-2023	Overall survival (OS) was defined as the time from the date of surgery to death

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026