AIM To investigate the clinical significance of preoperative systemic immune-inflammation index(SII) in patients with colorectal cancer(CRC). METHODS A retrospective analysis of 1383 cases with CRC was performed following radical surgery. SII was calculated with the formula SII =(P × N)/L, where P, N, and L refer to peripheral platelet, neutrophil, and lymphocyte counts, respectively. The clinicopathological features and follow-up data were evaluated to compare SII with other systemic inflammation-based prognostic indices such as the neutrophil-lymphocyte ratio(NLR) and platelet-lymphocyte ratio(PLR) in patients with CRC.RESULTS The optimal cut-off point for SII was defined as 340. The overall survival(OS) and disease-free survival(DFS) were better in patients with low NLR, PLR, and SII(P < 0.05). The SII was an independent predictor of OS and DFS in multivariate analysis. The area under the receiver-operating characteristics(ROC) curve for SII(0.707) was larger than those for NLR(0.602) and PLR(0.566). In contrast to NLR and PLR, SII could effectively discriminate between the TNM subgroups. CONCLUSION SII is a more powerful tool for predicting survival outcome in patients with CRC. It might assist the identification of high-risk patients among patients with the same TNM stage. AIM To investigate the clinical significance of preoperative systemic immune-inflammation index (SII) in patients with colorectal cancer (CRC). METHODS A retrospective analysis of 1383 cases with CRC was performed following radical surgery. SII was calculated with the formula SII = (P × N) / L, where P, N, and L refer to peripheral platelet, neutrophil, and lymphocyte counts, respectively. The clinicopathological features and follow-up data were evaluated to compare SII with other systemic inflammation-based prognostic indices such as the The overall survival (OS) and disease-free survival (DFS) were better The patients under low NLR, PLR, and SII (P <0.05). The SII was an independent predictor of OS and DFS in multivariate analysis. The area under the receiver-operating characteristics (ROC) curve for SII (0.707) was larger than those for NLR (0.6 02) and PLR (0.566). In contrast to NLR and PLR, SII could effectively discriminate between the TNM subgroups. CONCLUSION SII is a more powerful tool for predicting survival outcome in patients with CRC. It might assist the identification of high-risk patients among patients with the same TNM stage.