■这项研究的目的是开发一种简单有效的预测模型,用于通过选择与乳腺癌相关的临床和超声特征来计算乳腺癌的概率。
■3月1日解放军总医院超声科304名成年女性共402个病灶,2020年4月1日,2021年,被前瞻性地收集为开发小组。验证组包括从4月1日起在我们体检中心的98名患者的121个病灶,2021年3月1日2022年。应用最小绝对收缩和选择算子(LASSO)选择临床和超声变量,并应用R语言构建了Web版的交互式动态列折线图。通过验证组和乳腺成像报告和数据系统(BI-RADS)类别验证了预测模型。校准,通过R2、受试者工作特征(ROC)和决策曲线分析(DCA)评估差异和有效性,分别。
■在排除和随访后,发展组包括一百七十九个恶性病变和223个良性病变,而62个恶性病变和59个良性病变纳入验证组。年龄,流血的乳头溢液,不规则形状,不规则边界,异质回波,微钙化,衰减效应,周围组织的回声减少,导管中的病变,淋巴结形态异常,选择滋养血管和滋养血管抵抗指数(RI)大于0.70为独立危险因素。预测模型与BI-RADS类别之间的发展组的曲线下面积(AUC)没有显着差异(0.959vs.0.953,P>0.05),以及验证组(0.952vs.0.932,P>0.05)。对于预测模型,开发和验证组的R2分别为0.78和0.72。DCA显示,开发组的净收益(NB)高于验证组(0-100%vs.0-90%)。
■开发了具有临床和超声特征的预测模型,用于精确和直观的乳腺癌概率。这为进一步检验提供了可靠的参考。
UNASSIGNED: The aim of this study was to develop a simple and effective prediction model for calculating the probability of breast cancer by selecting clinical and sonographic features associated with breast cancer.
UNASSIGNED: A total of 402 lesions from 304 adult females from the ultrasound department of of PLA General Hospital from March 1st, 2020 to April 1st, 2021, were prospectively collected as the development group. The validation group included 121 lesions from 98 patients in our physical examination center from April 1st, 2021 to March 1st, 2022. Least absolute shrinkage and selection operator (LASSO) was applied to select clinical and ultrasonic variables, and R language was applied to build a web version of the interactive dynamic column line graph. The prediction model was validated by the validation group and the Breast Imaging Reporting and Data System (BI-RADS) categories. Calibration, differentiation and effectiveness were evaluated by R2, receiver operating characteristic (ROC) and decision curve analysis (DCA), respectively.
UNASSIGNED: One hundred and seventy-nine malignant lesions and 223 benign lesions were included in the development group after exclusion and follow-up, whereas 62 malignant lesions and 59 benign lesions were enrolled in the validation group. Age, bloody nipple discharge, irregular shape, irregular border, heterogeneous echo, microcalcification, attenuation effects, decreased echo in surrounding tissues, lesions in ducts, abnormal lymph node morphology, nourishing vessel and nourishing vessel\'s resistance index (RI) greater than 0.70 were selected as independent risk factors. There was no significant difference in the area under the curve (AUC) of the development group between the prediction model and the BI-RADS category (0.959 vs. 0.953, P>0.05), and so as the validation group (0.952 vs. 0.932, P>0.05). For the prediction model, R2 of the development and validation group was 0.78 and 0.72. The DCA showed that the net benefits (NB) of the development group were higher than that of the validation group (0-100% vs. 0-90%).
UNASSIGNED: A prediction model was developed with the clinical and ultrasonic features for the precise and intuitive probability of breast cancer. This could provide a reliable reference for further examination.