基于影像学表现和临床病理特征预测良性与交界性乳腺叶状肿瘤复发的列线图模型  

Nomogram based on clinicopathological and imaging features to predict recurrence of benign and borderline breast phyllodes tumor

作　　者：叶艳娜 叶瑞婷[2] 陈艳玲 彭雯 刘乐 肖文秋 黄辉 李明深 钟慕仪[2] 叶娴 Ye Yanna;Ye Ruiting;Chen Yanling;Peng Wen;Liu Le;Xiao Wenqu;Huang Hui;Li Mingshen;Zhong Muyi;Ye Xian(School of Health,Dongguan Vocational and Technical College,Dongguan 523000,China;Department of Breast Surgery,Dongguan People's Hospital/Tenth Afiliated Hospital of Southern Medical University,Dongguan 523059,China)

机构地区：[1]东莞职业技术学院卫生健康学院,523000 [2]东莞市人民医院/南方医科大学第十附属医院乳腺外科,523059

出　　处：《中华乳腺病杂志（电子版）》2023年第4期229-237,共9页Chinese Journal of Breast Disease(Electronic Edition)

摘　　要：目的:本研究探讨良性与交界性乳腺叶状肿瘤(PT)复发的潜在因素,构建列线图以预测PT复发率。方法:回顾性分析2016年6月至2019年12月在东莞市人民医院就诊的65例良性与交界性PT患者的临床病理及影像学资料,采取单因素及多因素Logistic回归分析其复发的独立危险因素,构建列线图。绘制受试者操作特征(ROC)曲线,计算曲线下面积(AUC);通过bootstrap建立校准曲线评估校准性能;通过决策曲线分析(DCA)证明该预测模型的临床实用性。结果:单因素Logistic回归分析显示发现与治疗间隔时间(TIMDT)>6个月、MRI强化方式不均匀、超声表现(肿瘤形态不规则、边缘不光整、分叶征、内回声不均匀、点状强回声、血流信号中等/丰富和囊性结构)与PT复发有关(P均<0.050)。多因素Logistic回归分析显示TIMDT>6个月(OR=32.230,95%CI:2.343~443.367,P=0.009)、MRI强化方式不均匀(OR=16.786,95%CI:1.030~273.431,P=0.048)及超声肿瘤分叶征(OR=14.861,95%CI:1.155~191.205,P=0.038)是PT复发的独立危险因素。根据这3个危险因素构建列线图,ROC曲线的AUC为0.906(95%CI:0.811~1.000),敏感度为83.3%,特异度为88.7%。校准曲线接近于理想曲线,拟合度较高。DCA曲线表明高风险阈值处于0.04~0.96时,使用该列线图预测PT复发的净获益率高。结论:TIMDT>6个月、MRI强化方式不均匀、具有超声肿瘤分叶征的良性与交界性乳腺PT患者复发风险较高。基于这3个因素开发的列线图预测PT复发能力较强,临床应用价值高。Objective:To explore the potential factors related to the recurrence of benign and borderline breast phyllodes tumor (PT) and establish a nomogram to predict the recurrence rate of PT.Methods:The clinicopathological and imaging data of 65 patients with benign and borderline PT who were treated in Dongguan People’s Hospital from June 2016 to December 2019 were retrospectively analyzed. The univariate and multivariate logistic regression were used to analyze the independent risk factors for recurrence, and a nomogram was constructed accordingly. The receiver operating characteristics (ROC) curve was drawn and the area under the curve (AUC) was calculated. A calibration curve was established by bootstrap method to evaluate calibration performance. The clinical utility of this predictive model was demonstrated by decision curve analysis (DCA).Results:Univariate logistic regression analysis showed that the time interval between mass discovery and treatment (TIMDT)>6 months, uneven MRI enhancement pattern, ultrasonic findings(irregular shape, uneven edge, tumor lobulation, uneven internal echo, punctate strong echo, moderate/abundant blood flow signal and cystic structure) were related to PT recurrence (all P<0.050). Multivariate logistic regression analysis showed that TIMDT>6 months (OR=32.230, 95%CI: 2.343-443.367, P=0.009), uneven MRI enhancement pattern (OR=16.786, 95%CI: 1.030-273.431, P=0.048) and ultrasonic tumor lobulation (OR=14.861, 95%CI: 1.155-191.205, P=0.038) were independent risk factors for PT recurrence. A nomogram was constructed based on these three independent risk factors. The AUC of ROC was 0.906 (95%CI: 0.811-1.000), the sensitivity was 83.3% and the specificity was 88.7%. The calibration curve of the model showed a good calibration efficiency. The DCA curve displayed high clinical net benefit from predicting PT recurrence at a threshold of 0.04-0.96.Conclusion:The benign and borderline breast PT patients with the following features (TIMDT>6 months, uneven MRI enhancement pattern, and ultrason

关 键 词：乳腺肿瘤 磁共振成像 超声检查 复发 列线图 叶状肿瘤 

分 类 号：R737.9[医药卫生—肿瘤]