基于临床影像学参数构建列线图模型在术前预测胃癌淋巴结转移中的价值

    Value of constructing nomogram model based on clinical-radiological parameters in preoperative prediction of lymph node metastasis in gastric cancer

    • 摘要:
      目的建立并验证基于临床影像学参数构建列线图模型在术前预测进展期胃癌(AGC)淋巴结转移中的价值。
      方法回顾性分析216例经病理证实的胃癌病人资料,随机分为训练组158例和验证组58例。收集病人临床资料及计算机断层成像(CT)影像学征象进行单因素、多因素logistic回归分析,用验证组进行验证,应用R 3.5.3软件包构建列线图模型,采用受试者工作特征(ROC)曲线评估列线图的预测效能,校准曲线及决策曲线验证模型的临床实用性。
      结果216例病人中,130例淋巴结转移阳性,86例淋巴结转移阴性。在训练组和验证组中,饮酒史、瘤周脂肪浸润、强化程度、CT-淋巴结状态和血小板与淋巴细胞比率(PLR)在术前胃癌病人发生淋巴结转移的预测中差异有统计学意义(P<0.05~P<0.01)。多因素logistic回归分析显示,病人饮酒史、瘤周脂肪浸润、CT强化程度、CT-淋巴结状态、PLR>161是术前预测胃癌病人发生淋巴结转移的独立影响因素(P<0.05)。基于饮酒史、瘤周脂肪浸润、CT强化程度、CT-淋巴结状态及PLR构建预测胃癌病人发生淋巴结转移的列线图模型,模型ROC曲线下面积在训练组和验证组分别为0.789(95%CI:0.719~0.860)、0.791(95%CI:0.678~0.905)。模型的敏感度及特异度在训练组分别为67.4%、78.3%,在验证组中分别为62.5%、84.6%,校准曲线和决策曲线证实了模型的临床实用性。
      结论饮酒史、瘤周脂肪浸润、CT强化程度、CT-淋巴结状态及PLR是胃癌病人发生淋巴结转移的独立影响因素,以此构建的列线图模型预测效能较好,在一定程度上可以协助临床决策。

       

      Abstract:
      ObjectiveTo construct and validate the value of constructing nomogram model based on clinical-radiological parameters in preoperative prediction of lymph node metastasis in advanced gastric cancer (AGC).
      MethodsA retrospective analysis was conducted on 216 gastric cancer patients confirmed by pathology, who were randomly divided into a training group (n=158) and a validation group (n=58). The clinical data and computed tomography (CT) imaging features of patients were collected for univariate and multivariate logistic regression analysis, the validation group was used to validate, the nomogram model was constructed with R 3.5.3 software package, the prediction efficacy of the nomogram model was evaluated using receiver operating characteristic (ROC) curve, and the clinical practicality of the model was validated by calibration curve and decision curve.
      ResultsAmong the 216 patients, 130 cases were positive for lymph node metastasis and 86 cases were negative for lymph node metastasis. In the training group and validation group, there were statistically significant differences in alcohol consumption history, peritumoral fat infiltration, degree of enhancement, CT-lymph node status, and platelet to lymphocyte ratio (PLR) in preoperative prediction of lymph node metastasis in gastric cancer patients (P<0.05 to P<0.01). Multivariate logistic regression analysis showed that alcohol consumption history, peritumoral fat infiltration, CT enhancement degree, CT-lymph node status, and PLR>161 were independent influencing factors for preoperative prediction of lymph node metastasis in gastric cancer patients (P<0.05). A namogram model was constructed to predict lymph node metastasis in gastric cancer patients based on alcohol consumption history, peritumoral fat infiltration, CT enhancement degree, CT-lymph node status, and PLR. The area under the ROC curve of the model was 0.789 (95%CI: 0.719-0.860) in the training group and 0.791 (95%CI: 0.678-0.905) in the validation group, respectively. The sensitivity and specificity of the model were 67.4% and 78.3% in the training group, and 62.5% and 84.6% in the validation group, respectively. The calibration curve and decision curve confirmed the clinical practicality of the model.
      ConclusionsAlcohol consumption history, peritumoral fat infiltration, CT enhancement degree, CT-lymph node status, and PLR are independent influencing factors for the occurrence of lymph node metastasis in gastric cancer patients. The namogram model constructed based on them has good prediction efficacy and can assist clinical decision-making to some extent.

       

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