Condition: Colorectal Liver Metastasis (CRLM) · Sponsor: Cancer Institute and Hospital, Chinese Academy of Medical Sciences
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.
This description comes directly from the study's public registry record.
HONG ZHAO, MD · +8613381106850 · zhaohong@cicams.ac.cn
Qichen Chen, MD · +8618810550822 · chenqichen0822@126.com
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| No. 17, South Panjiayuan, Chaoyang District, Beijing, Cancer Hospital, Chinese Academy of Medical Sciences, China | Beijing, Beijing Municipality, China | Recruiting |
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Source record: clinicaltrials.gov/study/NCT07027605