Development and Validation of an Artificial Intelligence Prediction Model and a Survival Risk Stratification for Lung Metastasis in Colorectal Cancer From Highly Imbalanced Data
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 2,779
- 主要终点
- lung metastasis
研究概览
简要总结
Background:
To assist clinicians with diagnosis and optimal treatment decision-making, we attempted to develop and validate an artificial intelligence prediction model for lung metastasis (LM) in colorectal cancer (CRC) patients.
Method:
The clinicopathological characteristics of 46037 CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 2779 CRC patients from a multi-center external validation set were collected retrospectively. After feature selection by univariate and multivariate analyses, six machine learning (ML) models, including logistic regression, K-nearest neighbor, support vector machine, decision tree, random forest, and balanced random forest (BRF), were developed and validated for the LM prediction. The optimization model with best performance was compared to the clinical predictor. In addition, stratified LM patients by risk score were utilized for survival analysis.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •patients with pathologic confirmation of a primary CRC diagnosis
排除标准
- •(1) patients with multiple primary cancers or other malignancies; (2) patients identified via autopsy or death certificate; and (3) patients with uncertain clinical data values
结局指标
主要结局
lung metastasis
时间窗: through study completion, an average of 3 month
diagnosed with lung metastasis
次要结局
未报告次要终点
研究者
Xishan Wang
the Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College
Peking Union Medical College