A Multi-Reader Multi-Case Controlled Clinical Trial to Evaluate the Performance Improvement From Computer-aided Tool for the Prognostic Prediction of Colorectal Liver Metastases
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 166
- 试验地点
- 1
- 主要终点
- AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
研究概览
简要总结
This study evaluates the impact of a novel computer-aided prognostic prediction tool for colorectal liver metastases (CRLM) on clinician performance. Colorectal cancer is a leading cause of cancer-related mortality worldwide, with 20-30% of patients presenting synchronous liver metastases, which are associated with poor prognosis and high postoperative recurrence rates. Simultaneous resection of primary tumor and liver metastases is a preferred treatment for selected patients but outcomes vary significantly. The latest web-based tool uses Random Forest models integrating demographic, clinical, laboratory, and genetic data to predict postoperative recurrence and mortality specifically for CRLM patients undergoing simultaneous resection. This multiple-reader, multiple-case (MRMC) study will assess 12 physicians who will predict 1-, 3-, and 5-year recurrence and mortality risks in 166 retrospective cases, with and without the tool's aid, separated by a washout period. The primary focus is to determine whether the tool improves prediction accuracy for 3-year postoperative mortality, measured by AUC-ROC. Secondary and exploratory endpoints include other time points, sensitivity, specificity, inter-rater reliability, decision-making confidence, and evaluation time. By enabling individualized risk assessment, this tool aims to support optimized clinical decision-making and tailored treatment strategies for CRLM patients undergoing simultaneous resection.
详细描述
This study aims to evaluate the impact of a novel computer-aided prognostic prediction tool on clinician performance in managing patients with colorectal liver metastases (CRLM). Colorectal cancer remains one of the leading causes of cancer-related mortality worldwide, with approximately 20-30% of patients presenting synchronous liver metastases at diagnosis. These metastases are associated with poor prognosis and a high rate of postoperative recurrence.
For selected patients, simultaneous resection of the primary colorectal tumor and liver metastases is the preferred treatment approach, though clinical outcomes vary widely. To address this variability, the latest web-based prediction tool employs Random Forest machine learning models that integrate comprehensive demographic, clinical, laboratory, and genetic data. This tool is specifically designed to predict postoperative recurrence and mortality for CRLM patients undergoing simultaneous resection, enabling individualized risk assessment.
In this multiple-reader, multiple-case (MRMC) study, 12 physicians will independently evaluate 166 retrospective patient cases. Each physician will estimate the risk of disease recurrence and mortality at 1-, 3-, and 5-year time points, both with and without access to the prediction tool. These two assessment phases will be separated by a washout period to minimize bias.
The primary objective is to determine whether use of the tool improves the accuracy of predicting 3-year postoperative mortality, quantified by the area under the receiver operating characteristic curve (AUC-ROC). Secondary and exploratory endpoints include prediction accuracy at other time points, sensitivity, specificity, inter-rater reliability, clinician confidence in decision-making, and time required for evaluation.
By providing specific, data-driven risk estimates, this computer-aided prognostic tool aims to enhance clinical decision-making and support personalized treatment planning for CRLM patients undergoing simultaneous resection, ultimately striving to improve patient outcomes.
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
- •≥ 18 years old
- •confirmation of histologically diagnosed liver metastases of colorectal adenocarcinoma
- •receiving colorectal resection with simultaneous liver resection.
排除标准
- •presence of other malignancies
- •absence of follow-up data
- •patients who were followed up postoperatively for less than 5 years and had no occurrences of death.
结局指标
主要结局
AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)
时间窗: Up to approximately 120 months
The comparative accuracy of model aided versus unaided risk prediction of post-operative 3-year mortality assessed by readers. Under model aided condition, prediction model will estimate the overall survival (OS) rate at Year 3 for each individual patient. OS was defined as the time from the date of simultaneous resection to death due to any cause. Patients without death were censored at their last known alive date. The mortality data were retrospectively collected and the event status were known. Patients were followed up to approximately 120 months after simultaneous resection.
次要结局
- AUCs: Area Under the Receiver Operating Characteristic Curve (AUC-ROC)(Up to approximately 120 months)
- Sensitivity: the ratio of true positives to total (actual) positives.(Up to approximately 120 months)
- Specificity: the ratio of true negatives to total (actual) negatives.(Up to approximately 120 months)
- Inter-rater reliability: the consistency of ratings made by readers on the cases(Up to approximately 120 months)