NCT06102278已完成不适用
Machine Learning Models for Predicting Postoperative Peritoneal Metastasis After Hepatocellular Carcinoma Rupture
Chen Xiaoping1 个研究点 分布在 1 个国家目标入组 522 人开始时间: 2020年1月1日最近更新:
适应症
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 522
- 试验地点
- 1
- 主要终点
- overall survival
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 90 Years(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •(1) HCC confirmed by pathologists (2) two preoperative imaging findings suggestive of tumor rupture (3) R0 resection (4) first tumor detection -
排除标准
- •(1) previous antitumor therapy (2) combination of other types of tumors (3) incomplete clinical data
结局指标
主要结局
overall survival
时间窗: 2018-2023
Overall survival (OS) was defined as the time from the date of surgery to death
次要结局
未报告次要终点
研究者
Chen Xiaoping
Professor
Tongji Hospital
研究点 (1)
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