Abstract
PURPOSE: We aimed to construct a nomogram to predict personalized post-recurrence survival (PRS) among colorectal cancer liver metastasis (CRLM) patients with post-hepatectomy recurrence. METHODS: Colorectal cancer liver metastasis patients who received initial hepatectomy and had subsequent recurrence between 2001 and 2019 in Sun Yat-sen University Cancer Center from China were included in the study. Patients were randomly assigned to a training cohort and a validation cohort on a ratio of 2:1. Univariable analysis was first employed to select potential predictive factors for PRS. Then, the multivariable Cox regression model was applied to recognize independent prognostic factors. According to the model, a nomogram to predict PRS was established. The nomogram's predictive capacity was further assessed utilizing concordance index (C-index) values, calibration plots, and Kaplan-Meier curves. RESULTS: About 376 patients were finally enrolled, with a 3-year PRS rate of 37.3% and a 5-year PRS rate of 24.6%. The following five independent predictors for PRS were determined to construct the nomogram: the largest size of liver metastases at initial hepatectomy, relapse-free survival, CEA level at recurrence, recurrent sites, and treatment for recurrence. The nomogram displayed fairly good discrimination and calibration. The C-index value was 0.742 for the training cohort and 0.773 for the validation cohort. Patients were grouped into three risk groups very well by the nomogram, with 5-year PRS rates of 45.2%, 23.3%, and 9.0%, respectively (p < 0.001) in the training cohort and 36.0%, 9.2%, and 4.6%, respectively (p < 0.001) in the validation cohort. CONCLUSION: A novel nomogram was built and validated to enable the prediction of personal PRS in CRLM patients with post-hepatectomy recurrence. The nomogram may help physicians in decision making.