A Machine Learning Approach to Identify Patients With Resected Non-small-cell Lung Cancer With High Risk of Relapse
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 60
- 试验地点
- 1
- 主要终点
- Algorithm for disease free survival
研究概览
简要总结
Early-stage non small cell lung cancer represents 20-30% of all non small cell lung cancer and is characterized by a high survival probability after surgical resection. However, considering stage IA-IIIA non small cell lung cancer, a relapse rate of about 50% is observed, with a different survival probability on the basis of tumor node metastasis status, although patients within the same tumor node metastasis stage exhibit wide variations in recurrence rate. There are currently no validated prognostic biomarkers able to identify patients with a high risk of relapse.
详细描述
This study will use data from an already available cohort of patients enrolled in the Resting study (a project funded by TRANSCAN in 2018) as a training set and data from a new concurrent cohort as validation set.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patient with an early stage of non small cell lung cancer
- •Indication of surgical resection
- •Patient able to understand and give his consent
- •Patient affiliated to the health insurance
排除标准
- •Patient with another cancer in the last 5 years
- •Patient with an allergy to the contrast medium
- •Patient under legal protection
结局指标
主要结局
Algorithm for disease free survival
时间窗: 18 months
Analysis on a training cohort of resected early-stage non small cell lung cancer
次要结局
未报告次要终点