Novel prognostic prediction models for patients with stage IV colorectal cancer after concurrent curative resection

Background: We developed a prediction tool for recurrence and survival in patients with stage IV colorectal cancer (CRC) following surgically curative resection. Patients and methods: From January 1983 to December 2012, 113 patients with CRC and synchronous liver and/or lung metastatic CRC were investigated at the Osaka Medical Center for Cancer and Cardiovascular Diseases. All patients underwent curative resection of primary and metastatic lesions. In the group of patients who underwent surgery from 1983 to 2008, a Cox regression model was used to develop prediction models for 1-year, 3-year and 5-year cancer-specific survival (CSS) and relapse-free survival (RFS). In the other group of patients who underwent surgery from 2009 to 2012, the developed prediction model was validated. Results: Univariate analysis of clinicopathological factors showed that the following factors were significantly correlated with CSS and RFS: preoperative serum carcinoembryonic antigen level, tumour location, pathologically defined tumour invasion and lymph node metastasis, and synchronous metastatic lesions. Using these variables, novel prediction models predicting CSS and RFS were constructed using the Cox regression model with concordance indexes of 0.802 for CSS and 0.631 for RFS. The prediction models were validated by external data sets in an independent patient group. Conclusions: We developed novel and reliable personalised prognostic models, integrating tumour, node, metastasis (TNM) factors as well as the preoperative serum carcinoembryonic antigen level, tumour location and metastatic lesions, to predict patients' prognosis following surgically curative resection. This individualised prediction model may help clinicians in the treatment of postoperative stage IV CRC following surgically curative resection.