基于多维度指标建立预测模型在乳腺癌病人腋窝淋巴结转移的应用价值

目的探讨以多维度指标建立预测模型在乳腺癌病人腋窝淋巴结(ALN)转移的应用价值。方法回顾性选取242例单侧乳腺癌女性病人作为研究对象。以病理检测结果确认有无ALN转移，划分为转移组(n=66)和非转移组(n=176)。对比2组的临床资料，用多因素logistic回归分析乳腺癌病人ALN转移的危险因素并建立预测模型。应用ROC曲线分析模型的区分度，应用拟合优度检验模型的校准度。另选93例单侧乳腺癌女性病人用于模型的临床验证。结果多因素logistic回归分析显示，肿瘤边缘模糊(OR=1.912)、ALN皮质厚度厚(OR=2.789)、ALN短径短(OR=2.280)、ALN短径/长径的比值大(OR=3.773)、分级程度高(OR=2.101)、miRNA-203表达量高(OR=3.529)是乳腺癌病人ALN转移的危险因素(P < 0.05~P < 0.01)。根据危险因素得出预测模型方程:Prob =1/(e^-Y)，Y=-30.724+0.648×肿瘤边缘模糊+ 1.026×ALN皮质厚度+ 0.824×ALN短径+1.328×ALN短径/长径的比值+ 0.742×分级程度+ 1.261×miRNA-203表达量。ROC曲线分析显示模型预测乳腺癌病人ALN转移的AUC面积为0.889(95%CI: 0.840~0.934)，说明模型区分度较好；拟合优度检验χ2=2.06，P>0.05，说明模型无过拟合现象。预测模型在临床验证得到的灵敏度为88.46%、特异度为83.58%、准确率为84.95%。结论以血清miRNA-203表达量、肿瘤分级程度、肿瘤边缘及ALN的皮质厚度、短径、短径/长径的比值来构建的乳腺癌病人ALN转移的预测模型有一定价值。

Application value of prediction model based on multi-dimensional indicators in axillary lymph node metastasis in breast cancer patients

ObjectiveTo explore the application value of establishing a prediction model based on multi-dimensional indicators in axillary lymph node(ALN) metastasis in breast cancer patients.MethodsA total of 242 female patients with unilateral breast cancer were retrospectively selected as the research subjects.The presence or absence of ALN metastasis were confirmed by pathological test results.Patients were divided into metastatic group(n=66) and non-metastatic group(n=176).The clinical data of two groups were compared.Multivariate logistic regression analysis was used to analyze the risk factors of ALN metastasis in breast cancer patients and establish a prediction model.ROC curve was used to analyze the discrimination of the model, and goodness of fit was used to test the calibration of the model.Another 93 female patients with unilateral breast cancer were selected for clinical validation of the model.ResultsMultivariate logistic regression analysis showed that blurred tumor margin(OR=1.912), thick ALN cortex(OR =2.789), short ALN diameter(OR=2.280), large ratio of short ALN diameter to long ALN diameter(OR=3.773), high grade of pathological(OR=2.101), and high expression of miRNA-203(OR=3.529) were risk factors for ALN metastasis in breast cancer patients(P < 0.05 to P < 0.01).The prediction model equation derived from the risk factors was Prob =1/(e^-Y), Y=-30.724+0.648×tumor margin blur+1.026×ALN cortical thickness+0.824×ALN short diameter+1.328×ALN short diameter/long diameter ratio+0.742×pathological grade +1.261×miRNA-203 expression level.ROC curve analysis showed that the AUC area of ALN metastasis in breast cancer patients predicted by the model was 0.889(95%CI: 0.840-0.934), indicating that the model had good discrimination.Goodness of fit test was χ2=2.06, P>0.05, indicating that the model had no overfitting phenomenon.The sensitivity, specificity and accuracy of the prediction model were 88.46%, 83.58% and 84.95%, respectively.ConclusionsThe prediction model of ALN metastasis in breast cancer patients constructed by serum miRNA-203 expression, tumor pathological grade, tumor margin and cortical thickness of ALN, short diameter, and short diameter/long diameter ratio has certain value.