Abstract: Objective To analyze and explore the risk factors affecting the prognosis of CRC patients based on the preoperative neutrophil-to-lymphocyte ratio (NLR) and neutrophil-to-high-density lipoprotein ratio (NHR), and to establish a prognostic prediction model. 
Methods The clinical data of 160 patients who underwent radical resection of CRC in the Department of General Surgery, the Second Hospital of Lanzhou University were collected, and 137 patients with colorectal polyps or adenomas were selected as controls. Nonparametric rank-sum tests were used to determine baseline-level differences between groups. Receiver operating characteristic (ROC) curve drawn by SPSS 26.0 software was used to ascertain the optimal cut-off value of NLR and NHR. Multivariate analyses of overall survival (OS) and disease-free survival (DFS) were performed using COX hazard regression models. Survival analysis was performed using the Kaplan-Meier method. R4.2.1 software was used to build the Nomogram model and evaluate its differentiation, consistency, and decision curve. 
Results ①The baseline levels of NLR (P＜0.001) and NHR (P=0.004)in the cancer group were significantly higher than those in the polyp or adenoma group. ②The optimal cut-off values of NLR and NHR for OS were 3.26 and 2.95, respectively. ③In terms of clinicopathological features, NLR was only statistically significant with tumor site (P=0.002); there was significant difference between NHR and total cholesterol (P=0.04) and Ki67 protein (P=0.042). ④Multivariate COX analysis showed that CEA (P=0.036), NLR (P=0.001)，  and NHR (P＜0.039) were the independent risk factors for OS; NHR (P=0.007) and lymph node (P=0.023) invasion were the independent risk factors for DFS. ⑤Survival analysis showed that the prognosis of patients in the low NLR and NHR group was better than that of the high NLR and NHR group(P＜0.05). ⑥Two nomogram models built around OS and DFS had good accuracy and practicability in long-term survival prediction, which were consistent with the evaluation of different iation and consistency, and decision curve analysis. 
Conclusion The postoperative prediction model for OS and DFS of CRC patients constructed based on NLR and NHR integrates the effects of factors such as inflammation, immunity and cholesterol metabolism on the behavioral characteristics of malignant tumors, and is more comprehensive and balanced in the prognosis evaluation.

Key words: colorectal neoplasms, nomograms, prediction model