Prognostic Prediction Models for Liver Metastasis and Overall Survival in Colorectal Cancer Patients

Abstract

The objective of this study was to develop novel prediction models for liver metastasis-free survival (LMFS) and overall survival (OS) in colorectal cancer (CRC) patients following surgically curative resections. We developed novel prediction models for LMFS and OS in CRC patients following surgically curative resections. Using clinicopathologic factors, such models were constructed with concordance indices of 0.811 and 0.776 for LMFS and OS, respectively. Seven hundred seventy-six CRC patients presenting to the Osaka Medical Center for Cancer and Cardiovascular Diseases between January 2004 and December 2010 were retrospectively studied. The exclusion criteria were patients with preoperative treatment, synchronous distant metastasis, noncurative resection, and incomplete postoperative follow-up. Based on the analysis of clinicopathologic factors, the following factors had significant correlation with LMFS: preoperative serum carcinoembryonic antigen (pre-CEA), tumor invasion, lymph node metastasis, lymphatic invasion, and venous invasion. Using these variables, a novel prediction model was constructed by the Cox regression model with a concordance index (c-index) of 0.811 for LMFS. The following factors had a significant correlation with OS: age, pre-CEA, preoperative serum carbohydrate antigen 19-9, tumor location, pathologically defined tumor invasion, lymph node metastasis, and venous invasion. Using these variables, a prediction model was constructed with a c-index of 0.776 for OS. These models were validated by external datasets in an independent patient group. We demonstrated the utility of a novel personalized prognostic model for liver metastasis, integrating tumor node metastasis factors, pre-CEA, and histologic lymphovascular invasion to predict the prognosis. Such models can help clinicians in treating CRC patients postoperatively.