A predictive model for metastatic colorectal cancer based on immune cells and tumor markers

OBJECTIVE: This study aims to investigate the relationship between immune cell levels, tumor markers, and metastatic colorectal cancer (mCRC), evaluate their predictive efficacy, and construct a predictive model. METHOD: Retrospectively selected patients diagnosed with colorectal cancer (CRC) through pathological examination at Shanxi Cancer Hospital between January 2016 and December 2018. T-tests and chi-square tests were used to identify clinical and pathological characteristics associated with mCRC. Evaluate predictive performance using the ROC curve. A risk factor scoring system is constructed based on immune cell levels and tumor markers, categorizing patients into low-risk and high-risk groups according to their scores. Single-factor and multi-factor logistic regression analyses were employed to identify independent predictors and construct a nomogram. RESULTS: A total of 270 patients with CRC were included, including 45 cases of mCRC. Statistical analysis results indicate that peripheral blood laboratory indicators associated with mCRC include immune cell levels (Th, Tc, Th/Tc) and tumor markers (CEA, CA199, CA242, CA724, CA50). The risk factor scoring system revealed that the incidence of distant metastasis was significantly higher in the high-risk group than in the low-risk group (P < 0.001). Furthermore, logistic regression analysis results indicate that the risk factor score is an independent predictor of distant metastasis in CRC. CONCLUSION: A risk factor scoring system based on immune cell levels (Th, Tc, Th/Tc) and tumor markers (CEA, CA199, CA242, CA724, CA50) effectively predicts the occurrence of mCRC. This approach holds promise as a non-invasive tool for dynamic monitoring of distant metastasis risk in clinical practice.