ML Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture
- Conditions
- Peritoneal Metastasis
- Interventions
- Other: Peritoneal Metastasis
- Registration Number
- NCT06102278
- Lead Sponsor
- Chen Xiaoping
- 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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 522
(1) HCC confirmed by pathologists (2) two preoperative imaging findings suggestive of tumor rupture (3) R0 resection (4) first tumor detection -
(1) previous antitumor therapy (2) combination of other types of tumors (3) incomplete clinical data
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Training cohort Peritoneal Metastasis All cases were randomly grouped according to 7:3, with 70% defined as the training group Validation cohort Peritoneal Metastasis All cases were randomly grouped according to 7:3, with 30% defined as the validation group
- Primary Outcome Measures
Name Time Method overall survival 2018-2023 Overall survival (OS) was defined as the time from the date of surgery to death
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
🇨🇳Wuhan, Hubei, China