Copyright ©The Author(s) 2024.
World J Gastroenterol. Feb 21, 2024; 30(7): 663-672
Published online Feb 21, 2024. doi: 10.3748/wjg.v30.i7.663
Table 1 Overview of biological behavior assessment systems for colorectal cancer liver metastasis
Evaluation System
Components included
CRSFive clinical indicatorsWidely used; identifies high-risk patientsLimited evidence on improving outcomes for high-risk CRS patients[21-23]
CMSMolecular classification into 4 subtypesOffers nuanced view of diseaseApplication in identifying neoadjuvant treatment beneficiaries remains unexplored[24]
m-CSRAS gene status, size of liver metastases, lymph node status of the primary tumorEnhanced system compared to previous scoresLacks granularity in weighing diverse high-risk factors and does not account for chemotherapy sensitivity[29,30]
TBSCategorizes patients into low, intermediate, and high-risk groups based on tumor size and numberSuperior discriminatory abilityLimited by excluding chemotherapy as an evaluation parameter[31]
GAMEGenetic and morphological factorsOutperformed CRS in external validationPotential limitation in excluding chemotherapy as an evaluation parameter[33,34]
CERRIntegrates mTBS with additional parametersCERRMathematical complexity and abstract metrics pose challenges for widespread clinical application[35]
AI modelMachine learning-based model predicting recurrence risksRemarkable accuracy in predicting recurrence riskInherent limitations include model overfitting and the black-box nature, hindering seamless integration into clinical practice[36]