基于炎症标志物的Nomogram模型预测非小细胞肺癌患者术后生存率

Nomogram model based on inflammatory markers to predict postoperative survival rate of patients with non-small cell lung cancer

目的 探讨建立基于炎症标志物的列线图模型用于预测非小细胞肺癌(non-small cell lung cancer, NSCLC)患者在行根治性切除术后的预后价值。方法 回顾性分析2010年1月—2015年10月在浙江省台州医院行非小细胞肺癌根治术治疗的817例患者的临床资料,通过X-Tile软件确定外周血淋巴细胞与单核细胞比值(lymphocyte-to-monocyte ratio, LMR)以及中性粒细胞与淋巴细胞比值(neutrophil-lymphocyte ratio, NLR)、血小板与淋巴细胞比值(platelet-lymphocyte ratio, PLR)、血小板分布宽度(platelet distribution width,PDW)和红细胞分布宽度(red blood cell distribution width, RDW)的最佳临界值。对影响患者预后的临床因素进行单因素和多因素Cox分析,建立炎症标志物的列线图模型预测非小细胞肺癌患者术后的总体生存率(OS)。结果 多因素Cox分析显示,较高的NLR和RDW、年龄、T分期、N分期、神经侵犯是NSCLC患者OS的独立危险因素(P<0.05)。基于以上因素建立预测OS的Nomogram模型,c指数为0.752(95%CI:0.714~0.790),校准曲线与决策曲线分析都表明该模型有更好的精确度与临床效能。结论 术前高NLR和RDW是非小细胞肺癌患者OS的独立危险因素,基于炎症标志物与临床病理指标的Nomogram模型可以更准确地评估NSCLC患者术后的生存情况。

Objective To explore the prognostic value of establishing Nomogram model based on inflammatory markers to predict the prognosis of patients with non-small cell lung cancer(NSCLC) after radical resection. Methods The clinical data of 817 patients who underwent non-small cell lung cancer radical surgery in Taizhou Hospital of Zhejiang Province from January 2010 to October 2015 were analyzed retrospectively. The optimal critical values of lymphocyte-to-monocyte ratio(LMR), neutrophil-lymphocyte ratio(NLR), platelet-lymphocyte ratio(PLR),platelet distribution width(PDW), and red blood cell distribution width(RDW) were determined by X-Tile software. The clinical factors affecting the prognosis of patients were analyzed by univariate and multivariate Cox analysis, and the Nomogram model of inflammatory markers was established to predict the overall survival rate(OS) of patients with non-small cell lung cancer after surgery. Results Multivariate Cox analysis showed that higher NLR, RDW, age, T stage, N stage, and nerve invasion were independent risk factors for OS in NSCLC patients(P<0.05).Based on the above factors, a Nomogram model was established to predict OS. The c index was 0.752(95% CI: 0.714-0.790). The calibration curve and decision curve analysis showed that the model had better accuracy and clinical efficacy.Conclusions Preoperative high NLR and RDW are independent risk factors for OS in patients with non-small cell lung cancer. The Nomogram model based on inflammatory markers and clinical pathological indicators can more accurately evaluate the survival of NSCLC patients after surgery.