摘要
目的:探索构建适用于术前诊断良性与恶性乳腺叶状肿瘤(phyllode tumor of the breast,PTB)的预测模型。方法:回顾性分析2011年1月—2018年12月哈尔滨医科大学附属肿瘤医院收治的且术前于该院进行多次(≥2次)超声随诊观察的69例良性PTB患者和41例恶性PTB(24例为交界性,17例为恶性)患者的临床病理资料,利用多因素Logistic回归分析确定的影响因素构建良性与恶性PTB术前预测模型;使用受试者操作特征(receiver operating characteristic,ROC)曲线评估该预测模型的效能;另选取2019年1月—2022年4月该院收治的22例良性PTB患者与19例恶性PTB(12例交界性,7例恶性)患者的临床病理资料进行外部验证。结果:logistic回归分析显示:肿瘤生长速度>2 mm/month和超声BIRADS分级≥4b类是诊断恶性PTB的独立预测因素(OR:4.476,95%CI:1.673~11.975;OR:9.448,95%CI:3.149~28.345;P<0.01)。得到logistic回归方程Logit(P)=-1.868+1.499×肿瘤生长速度+2.246×超声BI-RADS分级。训练队列的AUC为0.795(95%CI:0.699~0.890),最佳截断值是0.421,对应的灵敏度为0.732,特异度为0.826,约登指数为0.558,P<0.001。验证队列的AUC为0.772(95%CI:0.624~0.919),灵敏度为0.526,特异度为0.773,阳性预测值为0.667,阴性预测值为0.654,P=0.003。训练队列和验证队列的AUC均>0.75,说明该模型具有一定的预测能力。结论:使用临床病理指标构建的预测模型可用于术前诊断良性和恶性乳腺叶状肿瘤,为临床医师选择合适的手术切除范围提供一定的参考价值。
Objective:To establish a predictive model for preoperative diagnosis of benign and malignant phyllodes tumor of the breast(PTB).Methods:The clinicopathological data of 69 patients with benign PTB and 41 patients with malignant PTB(24 borderline and 17 malignant)who underwent multiple(≥2)preoperative ultrasound follow-ups in the Cancer Hospital of Harbin Medical University from January 2011 to December 2018 were retrospectively analyzed.The preoperative prediction models of benign and malignant PTB were constructed by using the influencing factors determined by multivariate logistic regression analysis.The receiver operating characteristic(ROC)curve was used to evaluate the efficiency of the prediction model.In addition,the clinicopathological data of 22 patients of benign PTB and 19 patients of malignant PTB(12 borderline and 7 malignant)admitted to the hospital from January 2019 to April 2022 were selected for external verification.Results:Logistic regression analysis showed that growth rate of tumor>2 mm/month and ultrasound BI-RADS category≥4b were independent predictors for the diagnosis of malignant PTB(OR:4.476,95%CI:1.673~11.975;OR:9.448,95%CI:3.149~28.345;P<0.01).The logistic regression equation:Logit(P)=-1.868+1.499×growth rate of tumor+2.246×ultrasound BI-RADS category.The AUC for the training cohort was 0.795(95%CI:0.699~0.890),the best cut-off value was 0.421,the corresponding sensitivity was 0.732,the specificity was 0.826,and the Jorden index was 0.558,P<0.001.The AUC for the the validation cohort was 0.772(95%CI:0.624~0.919),with the sensitivity of 0.526 and the specificity of 0.773,positive predictive value was 0.667 and negative predictive value was 0.654,P=0.003.The AUC of the training cohort and the validation cohort were both>0.75,indicating that the model has certain predictive ability.Conclusion:The predictive model constructed by clinicopathological parameters can be used for preoperative diagnosis of benign PTB and malignant PTB,and provide a certain reference value for clinicians to select the appropriate surgical resection scope.
作者
刘家霖
张显玉
南丁阿比雅思
张思亮
孟巍
庞达
LIU Jialin;ZHANG Xianyu;NANDING Abiyasi;ZHANG Siliang;MENG Wei;PANG Da(Department of Breast Surgery,Harbin Medical University Cancer Hospital,Harbin 150000,China;Department of Pathology,Harbin Medical University Cancer Hospital,Harbin 150000,China;Department of Radiology,Harbin Medical University Cancer Hospital,Harbin 150000,China;Department of Radiation Oncology,Harbin Medical University Cancer Hospital,Harbin 150000,China)
出处
《肿瘤》
CAS
北大核心
2023年第2期106-113,共8页
Tumor
关键词
乳腺叶状肿瘤
肿瘤生长速度
BI-RADS分级
鉴别诊断
Phyllodes tumor of breast(PTB)
Growth rate of tumor
Ultrasound BI-RADS category
Differential diagnosis
