基于术前NLR及NHR构建结直肠癌患者术后预测模型

doi:10.3969/j.issn.1007-3205.2023.08.010

摘要/Abstract

摘要： 目的基于术前中性粒细胞与淋巴细胞比值（neutrophiltolymphocyte ratio，NLR）及中性粒细胞与高密度脂蛋白比值（neutrophil to high-density lipoprotein ratio，NHR）分析并探讨影响结直肠癌（colorectal cancer，CRC）患者预后的风险因素，建立预后预测模型。
方法收集在兰州大学第二医院普通外科行CRC根治术的患者160例的临床资料，并选取137例结直肠息肉/腺瘤患者作为对照。使用非参数秩和检验判断2组间基线水平差异。应用SPSS 26.0软件绘制受试者工作特征曲线获取NLR及NHR的最优截断值。使用COX风险回归模型进行总生存期（overall survival，OS）及无病生存期（disease-free survival，DFS）的多因素分析。使用Kaplan-Meier法进行生存分析。R 4.2.1软件用于Nomogram模型构建，并对其进行区分度、一致性及决策曲线评价。
结果 ①NLR（P＜0.001）及NHR（P=0.004）在癌症组中基线水平显著高于息肉/腺瘤组。②NLR及NHR最优截断值分别为3.26、2.95。③临床病理特征：NLR仅与肿瘤部位（P=0.002）存在统计学意义；NHR与总胆固醇（P=0.04）及Ki67蛋白（P=0.042）存在统计学意义。④多因素COX分析显示CEA（P=0.036）、NLR（P=0.001）及NHR（P＜0.039）是影响OS的独立危险因素；NHR（P=0.007）和淋巴结侵犯（P=0.023）是影响DFS的独立危险因素。⑤生存分析显示NLR及NHR低值组患者预后均优于高值组（P＜0.05）。⑥围绕OS及DFS建立的两种Nomogram模型在远期生存预测方面具有较好的准确度和实用性，区分度、一致性评价及决策曲线分析均支持上述。
结论基于NLR及NHR构建的关于OS及DFS的CRC患者术后预测模型综合了炎症、免疫及胆固醇代谢等因素在恶性肿瘤行为特征方面的影响，在预后评估中更加全面与均衡。

关键词: 结直肠肿瘤, 列线图, 预测模型

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

杨驰, 罗长江. 基于术前NLR及NHR构建结直肠癌患者术后预测模型 [J]. 河北医科大学学报, 2023, 44(8): 920-928.

YANG Chi, LUO Chang-jiang. Construction of postoperative prediction model for colorectal cancer patients based on preoperative NLR and NHR[J]. Journal of Hebei Medical University, 2023, 44(8): 920-928.

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基于术前NLR及NHR构建结直肠癌患者术后预测模型

Construction of postoperative prediction model for colorectal cancer patients based on preoperative NLR and NHR

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