摘要
目的 基于多维度指标构建预测乳腺癌术后复发的列线图模型。方法 回顾性选取2014年3月—2020年4月在本院接受手术治疗的313例单侧乳腺癌女性患者为研究对象,采用随机数字表法按7∶3的比例将患者分为建模集219例和验证集94例。在建模集中,以术后随访复发情况将患者分为复发组与非复发组。采用单因素和多因素Logistic回归模型分析乳腺癌术后复发的危险因素。基于筛选结果采用R软件绘制列线图预测模型。采用受试者工作特征(ROC)曲线和拟合优度偏差性检验评价模型的表现。采用计算机模拟重复采样法(Bootstrap)验证并绘制校准图;采用决策曲线评价模型的临床获益率。结果 建模集219例乳腺癌患者术后复发63例(28.77%)。肿瘤边缘不规则(OR=1.692, 95%CI:1.154~3.794)、Shell功能和描迹法测量距病灶3 mm范围组织的最大弹性模量值(Shell3 E_(max))高(OR=2.869, 95%CI:1.795~5.392)、淋巴结转移(OR=2.071, 95%CI:1.486~4.578)、D-二聚体高表达(OR=2.264, 95%CI:1.574~5.307)、纤维蛋白原与白蛋白比值高(OR=3.089, 95%CI:2.053~6.156)是乳腺癌患者术后复发的危险因素(P<0.05)。基于上述5个因素构建风险预测列线图模型,模型的ROC曲线的曲线下面积为0.872(95%CI:0.829~0.917),最佳截断值(阈概率)为0.32(32%),对应的灵敏度、特异度分别为0.871、0.837;拟合优度检验表明预测模型不存在过拟合现象(χ^(2)=4.204,P=0.826);Bootstrap法自1 000次抽样验证发现校准曲线的平均绝对误差为0.019,表明预测模型具有良好的一致性。列线图模型预测验证集的ROC曲线的曲线下面积为0.864,灵敏度为0.862,特异度为0.815;校正曲线贴近于理想曲线。当决策曲线中的阈概率值设定为32%时,建模集与验证集人群的临床获益率分别为56%、62%。结论 基于乳腺癌患者的肿瘤边缘、Shell3 E_(max)值、淋巴结转移情况、血清D-二聚体、纤维蛋白原与白蛋白比值构建�
Objective To establish a Nomogram model for prediction of recurrence after breast cancer surgery based on multi-dimensional indicators.Methods A total of 313 female patients with surgical treatment for unilateral breast cancer from March 2014 to April 2020 in authors′hospital were retrospectively selected as research objects,and they were divided into modeling set with 219 cases and validation set with 94 cases by the random number table method at a ratio of 7 to 3.In the modeling set,the patients were divided into recurrence group and non-recurrence group according to recurrence condition during follow-up after operation.Single factor and multi-factor Logistic regression models were used to analyze the risk factors of postoperative recurrence of breast cancer.Based on the screening results,the R software was used to draw the Nomogram prediction model.The performance of the model was evaluated by the receiver operating characteristic(ROC)curve and deviation test of goodness of fit.The calibration map was verified and drawn by computer-simulated repeated sampling method(Bootstrap);the decision curve was used to evaluate the clinical benefit rate of the model.Results Among the 219 case in the modeling set,63 cases(28.77%)had recurrence of breast cancer after surgery.Irregular tumor margin(OR=1.692,95%CI,1.154 to 3.794),high maximum elastic modulus of tissues around 3 mm from focus measured by Shell function and tracing method(Shell3 E_(max))(OR=2.869,95%CI,1.795 to 5.392),lymph node metastasis(OR=2.071,95%CI,1.486 to 4.578),high expression of D-dimer(OR=2.264,95%CI,1.574 to 5.307)and high ratio of fibrinogen to albumin(OR=3.089,95%CI,2.053 to 6.156)were risk factors for postoperative recurrence of patients with breast cancer(P<0.05).Nomogram model for risk prediction was established based on the five factors mentioned above,the area under the curve of the ROC curve of the model was 0.872(95%CI,0.829 to 0.917),the best cut-off value(threshold probability)was 0.32(32%),and the corresponding sensitivity and specific
作者
朱婷
周海兰
华骁帆
ZHU Ting;ZHOU Hailan;HUA Xiaofan(Department of Ultrasound,Suzhou City Ninth People′s Hospital in Jiangsu Province,Suzhou,Jiangsu,215200;Department of General Surgery,Suzhou City Ninth People′s Hospital in Jiangsu Province,Suzhou,Jiangsu,215200)
出处
《实用临床医药杂志》
CAS
2023年第5期43-48,共6页
Journal of Clinical Medicine in Practice
关键词
列线图模型
超声特征
剪切波弹性成像
乳腺癌
复发风险
预测价值
Nomogram model
ultrasonic characteristics
shear wave elastography
breast cancer
risk of recurrence
prediction value
