背景:研究的目的是研究外周血指标在预测接受袖状肺叶切除术(SL)的中央型非小细胞肺癌(NSCLC)患者的生存和复发中的价值。
方法:我们收集了2014年1月至2023年5月在我们的机构接受SL治疗的146例NSCLC患者的临床信息。外周血中性粒细胞淋巴细胞比率(NLR),单核细胞淋巴细胞比率(MLR),通过受试者工作特征(ROC)曲线确定血小板淋巴细胞比率(PLR)水平,以建立阈值点。采用Kaplan-Meier生存分析评估不同分组的预后价值。并进行单变量和多变量Cox比例风险模型(简称COX).
结果:通过ROC分析进行无病生存期(DFS)和总生存期(OS)截止值。Kaplan-Meier生存分析显示NLR的OS存在显着差异(≥2.196vs.<2.196,p=0.0009),MLR(≥0.2763vs.<0.2763,p=0.0018),和PLR(≥126.11vs.<126.11,p=0.0354)。同样,NLR的DFS存在显着差异(≥3.010vs.<3.010,p=0.0005),MLR(≥0.2708vs.<0.2708,p=0.0046),和PLR(≥126.11vs.<126.11,p=0.0028)。单变量Cox分析显示,NLR(风险比[HR]:2.469;95%置信区间[CI]:1.416-4.306,p<0.001),MLR(HR:2.192,95%CI:1.319-3.643,p=0.002)和PLR(HR:1.696,95%CI:1.029-2.795,p=0.038)与OS相关。多因素Cox分析显示NLR(HR:2.036,95%CI:1.072-3.864,p=0.030)是一个独立的OS风险变量。此外,pN阶段(HR:3.163,95%CI:1.660-6.027,p<0.001),NLR(HR:2.530,95%CI:1.468-4.360,p<0.001),MLR(HR:2.229,95%CI:1.260-3.944,p=0.006)和PLR(HR:2.249,95%CI:1.300-3.889,p=0.004)与DFS相关。多因素Cox分析显示,pN分期(HR:3.098,95%CI:1.619-5.928,p<0.001)是一个单独的DFS风险变量。
结论:研究表明,NLR,MLR,PLR在预测患有SL的中央型NSCLC的个体的生存和复发方面发挥着方便且具有成本效益的作用。
BACKGROUND: The goal of the research was to examine the value of peripheral blood indicators in forecasting survival and recurrence among people suffering central-type non-small cell lung cancer (NSCLC) undergoing sleeve lobectomy (SL).
METHODS: Clinical information was gathered from 146 individuals suffering from NSCLC who had SL at our facility between January 2014 and May 2023. Peripheral blood neutrophil lymphocyte ratio (NLR), monocyte lymphocyte ratio (MLR), and platelet lymphocyte ratio (PLR) levels were determined by receiver operating characteristic (ROC) curve to establish the threshold points. Kaplan-Meier survival analysis was employed to evaluate the prognostic value of different groupings, and both univariate and multivariate Cox proportional hazards model (referred to as COX) were performed.
RESULTS: The disease-free survival (DFS) and overall survival (OS) cutoff values were carried out via ROC analysis. Kaplan-Meier survival analysis revealed notable differences in OS for NLR (≥2.196 vs. <2.196, p = 0.0009), MLR (≥0.2763 vs. <0.2763, p = 0.0018), and PLR (≥126.11 vs. <126.11, p = 0.0354). Similarly, significant differences in DFS were observed for NLR (≥3.010 vs. <3.010, p = 0.0005), MLR (≥0.2708 vs. <0.2708, p = 0.0046), and PLR (≥126.11 vs. <126.11, p = 0.0028). Univariate Cox analysis showed that NLR (hazard ratio [HR]: 2.469; 95% confidence interval [CI]: 1.416-4.306, p < 0.001), MLR (HR: 2.192, 95% CI: 1.319-3.643, p = 0.002) and PLR (HR: 1.696, 95% CI: 1.029-2.795, p = 0.038) were correlated alongside OS. Multivariate Cox analysis showed that NLR (HR: 2.036, 95% CI: 1.072-3.864, p = 0.030) was a separate OS risk variable. Additionally, the pN stage (HR: 3.163, 95% CI: 1.660-6.027, p < 0.001), NLR (HR: 2.530, 95% CI: 1.468-4.360, p < 0.001), MLR (HR: 2.229, 95% CI: 1.260-3.944, p = 0.006) and PLR (HR: 2.249, 95% CI: 1.300-3.889, p = 0.004) were connected to DFS. Multivariate Cox analysis showed that pN stage (HR: 3.098, 95% CI: 1.619-5.928, p < 0.001) was a separate DFS risk variable.
CONCLUSIONS: The study demonstrates that NLR, MLR, and PLR play a convenient and cost-effective role in predicting survival and recurrence among individuals alongside central-type NSCLC having SL.