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Abstract：
OBJECTIVE: The objective of this study was to compare ultrasound features and establish a predictive nomogram for distinguishing between triple-negative breast cancer (TNBC) and non-TNBC.
METHODS: A retrospective cohort study.
METHODS: This study was conducted at Quanzhou First Hospital, a grade A tertiary hospital in Quanzhou, China, with the research data set covering the period from September 2019 to August 2023.
METHODS: The study included a total of 205 female patients with confirmed TNBC and 574 female patients with non-TNBC, who were randomly divided into a training set and a validation set at a ratio of 7:3.
METHODS: All patients underwent ultrasound examination and received a confirmatory pathological diagnosis. Nodules were classified according to the Breast Imaging-Reporting and Data System standard. Subsequently, the study conducted a comparative analysis of clinical characteristics and ultrasonic features.
RESULTS: A statistically significant difference was observed in multiple clinical and ultrasonic features between TNBC and non-TNBC. Specifically, in the logistic regression analysis conducted on the training set, indicators such as posterior echo, lesion size, presence of clinical symptoms, margin characteristics, internal blood flow signals, halo and microcalcification were found to be statistically significant (p<0.05). These significant indicators were then effectively incorporated into a static and dynamic nomogram model, demonstrating high predictive performance in distinguishing TNBC from non-TNBC.
CONCLUSIONS: The results of our study demonstrated that ultrasound features can be valuable in distinguishing between TNBC and non-TNBC. The presence of posterior echo, size, clinical symptoms, margin, internal flow, halo and microcalcification was identified as predictive factors for this differentiation. Microcalcification, hyperechoic halo, internal flow and clinical symptoms emerged as the strongest predictive factors, indicating their potential as reliable indicators for identifying TNBC and non-TNBC.
METHODS: A retrospective cohort study.
METHODS: This study was conducted at Quanzhou First Hospital, a grade A tertiary hospital in Quanzhou, China, with the research data set covering the period from September 2019 to August 2023.
METHODS: The study included a total of 205 female patients with confirmed TNBC and 574 female patients with non-TNBC, who were randomly divided into a training set and a validation set at a ratio of 7:3.
METHODS: All patients underwent ultrasound examination and received a confirmatory pathological diagnosis. Nodules were classified according to the Breast Imaging-Reporting and Data System standard. Subsequently, the study conducted a comparative analysis of clinical characteristics and ultrasonic features.
RESULTS: A statistically significant difference was observed in multiple clinical and ultrasonic features between TNBC and non-TNBC. Specifically, in the logistic regression analysis conducted on the training set, indicators such as posterior echo, lesion size, presence of clinical symptoms, margin characteristics, internal blood flow signals, halo and microcalcification were found to be statistically significant (p<0.05). These significant indicators were then effectively incorporated into a static and dynamic nomogram model, demonstrating high predictive performance in distinguishing TNBC from non-TNBC.
CONCLUSIONS: The results of our study demonstrated that ultrasound features can be valuable in distinguishing between TNBC and non-TNBC. The presence of posterior echo, size, clinical symptoms, margin, internal flow, halo and microcalcification was identified as predictive factors for this differentiation. Microcalcification, hyperechoic halo, internal flow and clinical symptoms emerged as the strongest predictive factors, indicating their potential as reliable indicators for identifying TNBC and non-TNBC.
摘要：
目的：本研究的目的是比较超声特征并建立用于区分三阴性乳腺癌（TNBC）和非TNBC的预测列线图。
方法：回顾性队列研究。
方法：本研究在泉州市第一医院进行,泉州市某三级甲等医院,中国,研究数据集涵盖2019年9月至2023年8月。
方法：本研究共纳入205例确诊TNBC的女性患者和574例非TNBC的女性患者，以7:3的比例随机分为训练集和验证集。
方法：所有患者均行超声检查，病理确诊。根据乳腺影像学报告和数据系统标准对结节进行分类。随后，对临床特征和超声特征进行了对比分析。
结果：在TNBC和非TNBC之间的多种临床和超声特征中观察到统计学上的显着差异。具体来说,在对训练集进行的逻辑回归分析中，后向回声等指标，病变大小,临床症状的存在，边缘特征，内部血流信号,晕和微钙化具有统计学意义(p<0.05)。然后将这些重要指标有效地纳入静态和动态列线图模型中，在区分TNBC和非TNBC方面表现出高预测性能。
结论：我们的研究结果表明，超声特征在区分TNBC和非TNBC方面是有价值的。后回声的存在，尺寸,临床症状,margin,内部流动,晕和微钙化被确定为这种分化的预测因素.微钙化,高回声光环，内流和临床症状是最强的预测因素，表明它们作为识别TNBC和非TNBC的可靠指标的潜力。
方法：回顾性队列研究。
方法：本研究在泉州市第一医院进行,泉州市某三级甲等医院,中国,研究数据集涵盖2019年9月至2023年8月。
方法：本研究共纳入205例确诊TNBC的女性患者和574例非TNBC的女性患者，以7:3的比例随机分为训练集和验证集。
方法：所有患者均行超声检查，病理确诊。根据乳腺影像学报告和数据系统标准对结节进行分类。随后，对临床特征和超声特征进行了对比分析。
结果：在TNBC和非TNBC之间的多种临床和超声特征中观察到统计学上的显着差异。具体来说,在对训练集进行的逻辑回归分析中，后向回声等指标，病变大小,临床症状的存在，边缘特征，内部血流信号,晕和微钙化具有统计学意义(p<0.05)。然后将这些重要指标有效地纳入静态和动态列线图模型中，在区分TNBC和非TNBC方面表现出高预测性能。
结论：我们的研究结果表明，超声特征在区分TNBC和非TNBC方面是有价值的。后回声的存在，尺寸,临床症状,margin,内部流动,晕和微钙化被确定为这种分化的预测因素.微钙化,高回声光环，内流和临床症状是最强的预测因素，表明它们作为识别TNBC和非TNBC的可靠指标的潜力。
