基于超声特征列线图模型预测乳腺叶状肿瘤Ki-67表达水平的价值

余丽惠

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基于超声特征列线图模型预测乳腺叶状肿瘤Ki-67表达水平的价值

临床研究 | 更新时间：2024-04-19

- 基于超声特征列线图模型预测乳腺叶状肿瘤Ki-67表达水平的价值
- Prediction value of Ki-67 expression level in breast phyllodes tumor based on ultrasonic characteristic nomogram model
- 临床超声医学杂志 2024年26卷第2期
- 作者机构：
  
  佛山市第一人民医院
- 作者简介：
- 基金信息：
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- 纸质出版日期：2024，
  
  网络出版日期：2024-3-4，
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余丽惠. 基于超声特征列线图模型预测乳腺叶状肿瘤Ki-67表达水平的价值[J]. 临床超声医学杂志, 2024,26(2).

yu li hui. Prediction value of Ki-67 expression level in breast phyllodes tumor based on ultrasonic characteristic nomogram model[J]. Journal of Clinical Ultrasound in Medicine, 2024,26(2).
余丽惠. 基于超声特征列线图模型预测乳腺叶状肿瘤Ki-67表达水平的价值[J]. 临床超声医学杂志, 2024,26(2). DOI：

yu li hui. Prediction value of Ki-67 expression level in breast phyllodes tumor based on ultrasonic characteristic nomogram model[J]. Journal of Clinical Ultrasound in Medicine, 2024,26(2). DOI：

摘要

目的:探讨基于超声特征构建的列线图模型对乳腺叶状肿瘤(PTB)Ki-67表达水平的预测价值。方法:回顾性分析119例经病理证实为PTB的超声影像学资料

根据Ki-67表达水平分为低表达组(Ki-67≤10%)82例和高表达组(Ki-67＞10%)37例。对比分析两组声像图特征的差异

包括最大径、纵横径比、形态、边缘、实质回声、囊变、钙化、后方回声、血流信号、阻力指数及收缩期峰值流速。以单因素分析及多因素Logistic回归分析筛选出预测Ki-67高表达水平的独立预测因子

基于独立预测因子构建联合列线图模型；采用Bootstrap 法进行内部验证并利用校准曲线判断模型的吻合度

绘制受试者工作特征曲线(ROC)评估模型的预测效能

以决策曲线分析模型的临床获益。结果:最大径、囊变、血流信号、收缩期峰值流速与PTB患者的Ki-67表达水平相关(P <0.05)

其中最大径(OR=0.642

95% CI:0.295～0.993)、囊变(OR=0.078

95% CI:0.008～0.808)和收缩期峰值流速(OR=1.404

95% CI:1.106～1.782)是预测Ki-67高表达水平的独立预测因子(P <0.05)。列线图模型量化独立预测因子显示预测效果与实际结果的一致性良好

一致性指数(C-index值)为0.814(95% CI:0.710～0.913)。ROC曲线分析表明独立预测因子的联合预测概率模型效能[曲线下面积(AUC)=0.812]优于各单独指标中的最大径(AUC=0.696)、囊变(AUC=0.705)及收缩期峰值流速(AUC=0.736)

且当阈值为0.10～0.48时

其临床获益较高。结论:利用超声特征构建的列线图模型可用于预测PTB患者的Ki-67 表达水平

该模型具有较高的准确性和可靠性。

Abstract

Objective: To explore the predictive value of nomogram model based on ultrasonic characteristics for Ki-67 expression in phyllodes tumor of breast (PTB).Methods: The ultrasonic imaging data of 119 cases of PTB confirmed by pathology were analyzed retrospectively

82 cases were divided into low expression group (Ki-67≤10%) and 37 cases were high expression group (Ki-67>10%) according to the expression level of Ki-67.The features of the two groups were compared and analyzed

including maximum diameter

aspect ratio

shape

edge

parenchymal echo

cystic change

calcification

rear echo

blood flow signal

resistance index and peak systolic flow rate.Independent predictors of Ki-67 high expression were selected by univariate analysis and multiple Logistic regression analysis

and a joint nomogram model was constructed based on the independent predictors. Bootstrap method was used for internal verification and calibration curve was used to judge the goodness of fit of the model. Receiver operating characteristic curve (ROC) was drawn to evaluate the predictive efficacy of the model

and the clinical benefit of the model was analyzed by decision curve.Results: The maximal diameter

cystic change

blood flow signal and systolic peak velocity were correlated with the expression level of Ki-67 in PTB patients (P<0.05)

among which the maximal diameter (OR=0.642

95% CI: 0.295 ~ 0.993)

cystic change (OR=0.078

95% CI: 0.008～0.808)and systolic peak flow rate (OR=1.404

95%CI: 1.106～1.782) were independent predictors of Ki-67 high expression level (P<0.05).The independent predictors quantified by the nomogram model showed a good agreement between the prediction effect and the actual results

and the agreement index (C-index value) was 0.814 (95%CI: 0.710 ~ 0.913).The ROC curve analysis showed that the combined prediction probability model efficiency of independent predictors [area under the curve (AUC) =0.812] was better than that of the maximum diameter (AUC=0.696)

sac change (AUC=0.705) and peak systolic flow rate (AUC=0.736)

and the clinical benefit was higher when the threshold was 0.10 ~ 0.48.Conclusion: The nomogram model based on ultrasound features can be used to predict the level of Ki-67 expression in PTB patients

and the model has high accuracy and reliability.

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