Clinical Significance of and Predictive Risk Factors for the Postoperative Elevation of Carcinoembryonic Antigen in Patients With Non-Metastatic Colorectal Cancer

Background: Recently a few researches focus on the correlation between postoperative carcinoembryonic antigen (post-CEA) and the outcome of colorectal cancer (CRC), but none investigates the predictive value of post-CEA in a prognostic model. Besides, current recommendations on the frequency of post-CEA surveillance are not individualized and well followed. There is an absence of identification of patients who are more likely to have abnormal post-CEA levels and need more frequent CEA measurements. Methods: Consecutive CRC patients who underwent curative surgery were enrolled and randomly divided into the discovery (n=352) and testing cohort (n=233). Impacts of preoperative CEA (pre-CEA) and post-CEA on prognosis were assessed. Cox regression model was applied to develop prognostic nomograms, which were validated by concordance index (C-index), calibration, and discrimination. Logistic regression was used to identify predictive risk factors for and construct the prediction model for post-CEA elevation. Results: Post-CEA independently predicted OS and DFS while pre-CEA did not. Post-CEA elevation represented higher risks in patients with normal pre-CEA than those with persistent elevated CEA. The nomograms for OS and DFS were established with body mass index, tumor differentiation, N stage, lymphocyte to monocyte ratio, and post-CEA. The nomograms showed good calibration and superior discrimination than TNM stage, with C-indices of 0.783 and 0.759 in the discovery set and 0.712 and 0.774 in the testing set for OS and DFS, respectively. The prediction model for post-CEA elevation was established with age, platelet to lymphocyte ratio, preoperative CA199, and pre-CEA. The AUC of the model in the two cohorts was 0.802 and 0.764, respectively. Conclusions: Elevated post-CEA strongly indicated poor prognosis. The addition of post-CEA significantly enhanced the performance of prognostic nomograms. And the prediction model for post-CEA elevation may help identify patients who should receive more intensive postoperative surveillance of CEA levels.