PDF(Pubmed)
Abstract：
In this study, We aim to explore the association between the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), lymphocyte to monocyte ratio (LMR) and prognostic nutritional index (PNI) and distant metastasis of gastric cancer and develop an efficient nomogram for screening patients with distant metastasis. A total of 1281 inpatients with gastric cancer were enrolled and divided into the training and validation set.Univariate, Lasso regression and Multivariate Logistic Regression Analysis was used to identify the risk factors of distant metastasis. The independent predictive factors were then enrolled in the nomogram model. The nomogram\'s predictive perform and clinical practicality was evaluated by receiver operating characteristics (ROC) curves, calibration curves and decision curve analysis. Multivariate Logistic Regression Analysis identified D-dimer, CA199, CA125, NLR and PNI as independent predictive factors. The area under the curve of our nomogram based on these factors was 0.838 in the training cohort and 0.811 in the validation cohort. The calibration plots and decision curves demonstrated the nomogram\'s good predictive performance and clinical practicality in both training and validation cohort. Therefore,our nomogram could be an important tool for clinicians in screening gastric cancer patients with distant metastasis.
摘要：
在这项研究中,我们的目的是探讨中性粒细胞与淋巴细胞比率(NLR)之间的关系，血小板与淋巴细胞比率（PLR），全身免疫炎症指数（SII），淋巴细胞与单核细胞比率（LMR）和预后营养指数（PNI）与胃癌远处转移的关系，并建立了筛选远处转移患者的有效列线图。共纳入1281例胃癌住院患者，分为训练集和验证集。单变量,采用Lasso回归和多因素Logistic回归分析确定远处转移的危险因素。然后将独立预测因子纳入列线图模型。通过受试者工作特征（ROC）曲线评估列线图的预测性能和临床实用性，校准曲线和决策曲线分析。多因素Logistic回归分析确定D-二聚体，CA199、CA125、NLR和PNI为独立预测因子。基于这些因素的列线图曲线下面积在训练队列中为0.838，在验证队列中为0.811。校准图和决策曲线表明列线图在训练和验证队列中具有良好的预测性能和临床实用性。因此,我们的列线图可能是临床医生筛查有远处转移的胃癌患者的重要工具.
