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.
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 the concordance index (C-index), calibration curve, and receiver operating characteristic curve (ROC) analysis. And prediction improvement of the nomograms was assessed with net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Logistic regression was used to identify predictive risk factors and construct the prediction model for post-CEA elevation.
Post-CEA independently predicted overall survival (OS) and disease-free survival (DFS), while pre-CEA did not. Post-CEA elevation represented higher risks in patients with normal pre-CEA, compared to 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 pTNM stage, with the C-index 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. Comparisons between models using IDI and NRI implied that the nomograms performed better than pTNM stage and the predictive power could be improved with the addition of post-CEA. The prediction model for post-CEA elevation was established with age, platelet-to-lymphocyte ratio, preoperative CA19-9, and pre-CEA. The AUC of the model in the two cohorts was 0.802 and 0.764, respectively.
Elevated post-CEA was a strong indicator of 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 ought to reasonably receive more intensive postoperative surveillance of CEA levels.