Development and validation of a prognostic nomogram for colorectal cancer after radical resection based on individual patient data from three large-scale phase III trials

BACKGROUND: Few prediction models have so far been developed and assessed for the prognosis of patients who undergo curative resection for colorectal cancer (CRC). MATERIALS AND METHODS: We prepared a clinical dataset including 5,530 patients who participated in three major randomized controlled trials as a training dataset and 2,263 consecutive patients who were treated at a cancer-specialized hospital as a validation dataset. All subjects underwent radical resection for CRC which was histologically diagnosed to be adenocarcinoma. The main outcomes that were predicted were the overall survival (OS) and disease free survival (DFS). The identification of the variables in this nomogram was based on a Cox regression analysis and the model performance was evaluated by Harrell's c-index. The calibration plot and its slope were also studied. For the external validation assessment, risk group stratification was employed. RESULTS: The multivariate Cox model identified variables; sex, age, pathological T and N factor, tumor location, size, lymphnode dissection, postoperative complications and adjuvant chemotherapy. The c-index was 0.72 (95% confidence interval [CI] 0.66-0.77) for the OS and 0.74 (95% CI 0.69-0.78) for the DFS. The proposed stratification in the risk groups demonstrated a significant distinction between the Kaplan–Meier curves for OS and DFS in the external validation dataset. CONCLUSIONS: We established a clinically reliable nomogram to predict the OS and DFS in patients with CRC using large scale and reliable independent patient data from phase III randomized controlled trials. The external validity was also confirmed on the practical dataset.