术前炎症评分对胃癌患者预后的影响

Impact of Preoperative Inflammation Score on the Prognosis of Patients with Gastric Cancer

目的:目前还缺乏对胃癌患者术后的NLR预测价值的研究。本研究旨在通过比较NLR与其他炎症标志物和肿瘤生物标志物的预后能力,确认NLR对胃癌患者预后的预测价值。方法:在这项回顾性分析中,研究了171名被诊断为胃癌患者的信息。研究检测了外周血中的各种标记物,包括中性粒细胞/淋巴细胞比值(NLR)、血小板/淋巴细胞比值(PLR)、淋巴细胞/单核细胞比值(LMR)、全身免疫炎症指数(SII)、预后营养指数(PNI)、癌抗原125 (CA125)、碳水化合物抗原19-9 (CA19-9)、碳水化合物抗原72-4 (CA72-4)、癌胚抗原(CEA)和甲胎蛋白(AFP)。为了确定每个参数的预后能力和最佳临界值,分析中使用了运行特征曲线和曲线下面积。为了评估独立的预后因素,我们采用了Kaplan-Meier曲线和多因素COX分析。多因素COX分析中的变量被用于构建提名图。结果:NLR的最佳截断值为3.35。高NLR组的总生存率明显低于低NLR组(P = 0.0045)。NLR-H组和NLR-L组之间的炎症指标存在显著差异,包括PLR (P < 0.001)、LMR (P < 0.001)、SII (P < 0.001)和PNI (P = 0.001)。多变量Cox确定NLR (P = 0.001)和CA125 (P = 0.004)是血液指标中唯一单独的预测变量。使用NLR建立的提名图在1年(AUC = 0.778)、3年(AUC = 0.773)和5年(AUC = 0.781)时显示出卓越的预测性能。交叉验证表明,该模型具有良好的预测性能和判别能力。结论:NLR是预测胃癌患者术后生存结果的一个简单而有效的指标,具有相当大的预测意义。基于NLR的列线图为患者提供了直观、准确的预后预测。

Objective: There is a lack of studies on the predictive value of NLR in gastric cancer patients after surgery. The aim of this study was to confirm the predictive value of NLR for the prognosis of pa-tients with gastric cancer by comparing the prognostic ability of NLR with other inflammatory markers and tumor biomarkers. Methods: In this retrospective analysis, information on 171 pa-tients diagnosed with gastric cancer was studied. Various markers in peripheral blood were exam-ined, including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lympho-cyte/monocyte ratio (LMR), systemic immune-inflammatory index (SII), prognostic-nutritional in-dex (PNI), carcinoma antigen 125 (CA125), and carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4), carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP). To determine the prognostic power and optimal threshold for each parameter, running characteristic curves and area under the curve were used in the analyses. To assess independent prognostic factors, we used Kaplan-Meier curves and multifactorial COX analyses. Variables from the multifactor COX analysis were used to construct nomograms. Results: The optimal cut-off value for NLR was 3.35. Overall survival was significantly lower in the high NLR group than in the low NLR group (P = 0.0045). There were significant differences in inflammatory indices between the NLR-H and NLR-L groups, including PLR (P < 0.001), LMR (P < 0.001), SII (P < 0.001) and PNI (P = 0.001). Multivariate Cox identified NLR (P = 0.001) and CA125 (P = 0.004) as the only separate predictor variables in the hematological metrics. Nomograms built using NLR showed excellent predictive performance at 1 year (AUC = 0.778), 3 years (AUC = 0.773) and 5 years (AUC = 0.781). Cross-validation showed that the model had good predictive performance and discriminative ability. Conclusion: NLR is a simple and effective predictor of postoperative survival outcomes in gastric cancer patients with consider-able predictive significance. The NLR-based column-line graph provides an intuitive and accurate prognostic prediction for patients.