摘要目的:基于术前中性粒细胞/淋巴细胞比值与γ-谷氨酰转肽酶/血小板比值(NLR-GPR)评分，构建预测肝细胞癌(HCC)患者肝切除术后预后的列线图模型。方法:回顾性分析2012年1月至2016年9月在浙江省台州医院接受根治性切除的284例HCC患者的临床资料，其中男性235例，女性49例，年龄57(51，65)岁。记录患者的性别、年龄、中性粒细胞计数、淋巴细胞计数、血小板计数、γ-谷氨酰转肽酶、总胆红素等临床资料。采用Cox比例风险回归模型评估术前NLR-GPR评分与患者无病生存期(DFS)及总生存期(OS)之间的关系，根据多因素分析结果构建列线图模型。生存曲线采用Kaplan-Meier法绘制，组间差异通过log-rank检验评估。模型性能通过一致性指数进行评估。结果:NLR-GPR评分与患者DFS及OS均呈负相关，评分越高，生存预后越差(均 P<0.05)。多因素分析显示，NLR-GPR评分是影响HCC患者DFS( HR＝1.463，95% CI：1.135~1.887， P＝0.003)和OS( HR＝1.734，95% CI：1.300~2.313， P<0.001)的危险因素。基于多因素Cox回归分析中筛选出的变量(包括术后胸腔积液、AJCC分期、血管侵犯及NLR-GPR评分)构建列线图模型，该列线图模型在预测准确性方面表现良好，其预测无病生存率和总生存率的一致性指数分别为0.676和0.726。 结论:基于术前NLR-GPR评分及相关临床病理因素构建的列线图模型，能够有效预测肝切除术后HCC患者的预后。

abstractsObjective:To develop a nomogram model based on the preoperative neutrophil-to-lymphocyte ratio and gamma-glutamyl transpeptidase (GGT) -to-platelet ratio (NLR-GPR) score to predict the prognosis of patients with hepatocellular carcinoma (HCC) undergoing hepatectomy.Methods:Clinical data of 284 patients with HCC who underwent curative resection at Taizhou Hospital of Zhejiang Province between January 2012 and September 2016 were retrospectively analyzed, including 235 males and 49 females, aged 57(51, 65) years. Clinical data, including gender, age, neutrophil count, lymphocyte count, platelet count, GGT, and total bilirubin, were collected. The Cox proportional hazards regression model was employed to assess the relationship between the preoperative NLR-GPR score and patient disease-free survival (DFS) and overall survival (OS). A nomogram was constructed based on the results of the multivariate analysis. Survival curves were generated using the Kaplan-Meier method, and differences between groups were evaluated using the log-rank test. The performance of the model was assessed by the concordance index (C-index).Results:The NLR-GPR score was found to be negatively correlated with both DFS and OS (both P<0.05), where a higher score indicated a poorer prognosis. Multivariate analysis identified the NLR-GPR score as an independent risk factor for both DFS ( HR=1.463, 95% CI: 1.135-1.887, P=0.003) and OS ( HR=1.734, 95% CI: 1.300-2.313, P<0.001). A nomogram was deve-loped based on the variables selected from the multivariate Cox regression analysis, including postoperative pleural effusion, AJCC stage, vascular invasion, and the NLR-GPR score. This nomogram demonstrated good predictive accuracy, with C-indices for DFS and OS of 0.676 and 0.726, respectively. Conclusion:The nomogram model, constructed based on the preoperative NLR-GPR score and relevant clinicopathological factors, can effectively predict the postoperative survival of patients with HCC undergoing hepatectomy.