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基于治疗前炎性反应指标构建食管鳞癌患者根治性放疗预后列线图模型

Construction of A Nomogram Prognostic Model Based on Pretreatment Inflammatory Indicator for Esophageal Squamous Cell Carcinoma Patients Treated with Radical Radiotherapy

  • 摘要:
    目的 探讨治疗前炎性反应指标对食管鳞癌(ESCC)患者根治性放疗疗效和预后预测价值。
    方法 收集接受根治性放疗的246例ESCC患者的临床资料。采用受试者工作特征(ROC)曲线计算血小板与淋巴细胞比值(PLR)、中性粒细胞与淋巴细胞比值(NLR)和全身免疫炎症指数(SII)的最佳截断值。采用Kaplan-Meier法进行生存分析,Cox比例风险回归模型进行单因素和多因素分析,R4.2.0软件构建列线图预测模型。
    结果 根据ROC曲线确定PLR、NLR和SII的最佳截断值分别为146.06、2.67和493.97。低NLR组和高NLR组的总缓解率(ORR)分别为77.6%和64.5%(P<0.05)。Kaplan-Meier生存分析显示,低PLR、NLR和SII组患者的生存预后均优于高PLR、NLR和SII组,差异均有统计学意义(均P<0.05)。多因素分析显示,性别、治疗方式、T分期和NLR均是影响患者总生存(OS)的独立预后因素,T分期和NLR是影响患者无进展生存(PFS)的独立预后因素(均P<0.05)。根据多因素分析构建ESCC患者OS和PFS的列线图预测模型,C指数分别为0.703和0.668,校准曲线表明列线图模型预测患者OS、PFS与实际观察结果之间具有较高的一致性。
    结论 治疗前PLR、NLR和SII与ESCC患者根治性放疗预后有关,NLR是OS和PFS的独立影响因素,基于NLR建立的列线图模型具有较好的预测能力。

     

    Abstract:
    Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy.
    Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors.
    Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS.
    Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

     

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