Blood cholesterol-to-lymphocyte ratio as a novel prognostic marker to predict postoperative overall survival in patients with colorectal cancer

BACKGROUND: Lipid disequilibrium and systemic inflammation are reported to correlate with tumorigenesis and development of colorectal cancer (CRC). We construct the novel biomarker cholesterol-to-lymphocyte ratio (CLR) to reflect the synergistic effect of cholesterol metabolism and inflammation on CRC outcomes. This study aims to investigate the clinical significance of CLR and establish a prognostic model for CRC. METHODS: Our study retrospectively enrolled 223 CRC patients who underwent curative surgical resection. The Kaplan-Meier method was employed to estimate the overall survival (OS) rates, and the association between serological biomarkers and survival was assessed with a log-rank test. Cox proportional hazard regression was applied in the univariate and multivariate analyses to identify independent prognostic factors, which were then used to develop a predictive nomogram model for OS in CRC. The nomogram was evaluated by the C-index, receiver operator characteristic curve (ROC) analysis, and calibration plot. All cases were grouped into three stratifications according to the total risk points calculated from the nomogram, and the difference in OS between them was assessed with the Kaplan-Meier method. RESULTS: At the end of the study, death occurred in 47 (21%) cases. Patients with low CLR (< 3.23) had significantly prolonged survival (P < 0.001). Multivariate analyses revealed that N stage (P < 0.001), harvested lymph nodes (P = 0.021), and CLR (P = 0.005) were independent prognostic factors for OS and a prognostic nomogram was established based on these variables. The nomogram showed good calibration and predictive performance with a superior C-index than TNM stage (0.755 (0.719–0.791) vs. 0.663 (0.629–0.697), P = 0.001). Patients of different risk stratifications based on the total score of nomogram showed distinct survival (P < 0.001). CONCLUSIONS: The nomogram based on CLR and other clinical features can be used as a potentially convenient and reliable tool in predicting survival in patients with CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-021-02471-4.