基于 US 和临床病理特征的提名图:结节阳性乳腺癌患者接受新辅助化疗后的腋窝结节评估

IF 2.9 3区 医学 Q2 ONCOLOGY Clinical breast cancer Pub Date : 2024-08-01 DOI:10.1016/j.clbc.2024.03.005
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引用次数: 0

摘要

开发一种方便的模式来预测乳腺癌患者对新辅助化疗(NAC)的腋窝反应。在这项多中心研究中,共有1019名经活检证实淋巴结(LN)阳性并接受新辅助化疗的乳腺癌患者按7:3的比例被随机分配到训练组和验证组。利用原发肿瘤和淋巴结的临床病理和超声(US)特征建立相应的预测模型,并生成一个整合了临床病理和US预测因子的提名图来预测腋窝对NAC的反应。47.79%的患者获得了腋窝病理完全反应(pCR)。雌激素受体、人表皮生长因子受体-2、Ki-67评分和临床结节分期的表达是预测NAC腋窝反应的独立指标。原发肿瘤的位置和放射学反应、皮质厚度和US上LN的形状也与结节pCR显著相关。在验证队列中,US 模型(AUC,0.76)的判别能力优于临床病理模型(AUC,0.68);组合模型(AUC,0.85)在预测结节 pCR 方面显示出很强的判别能力。基于组合模型的提名图校准曲线显示,预测结果与观察结果之间存在很大的一致性。该提名图显示所有患者的 FNR 为 16.67%,三阴性乳腺癌患者的 FNR 为 10.53%。包含常规临床病理和美国特征的提名图可以预测结节 pCR,是辅助乳腺癌患者 NAC 后腋窝治疗决策的工具。为了防止新辅助化疗(NAC)后淋巴结(LN)转化患者的腋窝手术过度治疗,准确的腋窝分期程序至关重要。这项多中心研究旨在开发一种简便的方法来预测乳腺癌患者对新辅助化疗的腋窝反应。共有 1019 名患者按 7:3 的比例被随机分配到训练组和验证组。原发肿瘤和腋窝淋巴结的US特征可独立预测乳腺癌患者对NAC的腋窝反应。在验证组中,US 模型(AUC,0.76)的判别能力优于临床病理模型(AUC,0.68);组合模型(AUC,0.85)在预测结节 pCR 方面显示出很强的判别能力。US 在鉴别更多腋窝 LN 对 NAC 无应答者方面确实可以发挥重要作用。利用现成的临床病理特征和 US 特征构建的提名图显示,所有患者的 FNR 为 16.67%,三阴性乳腺癌患者的 FNR 为 10.53%。该提名图有可能成为一种有价值的可视化工具,帮助临床医生做出明智的治疗决定,并优化接受 NAC 的结节后性乳腺癌患者(尤其是三阴性乳腺癌患者)的护理。
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Nomogram Based on US and Clinicopathologic Characteristics: Axillary Nodal Evaluation Following Neoadjuvant Chemotherapy in Patients With Node-Positive Breast Cancer

Background

To develop a convenient modality to predict axillary response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

Materials and Methods

In this multi-center study, a total of 1019 breast cancer patients with biopsy-proven positive lymph node (LN) receiving NAC were randomly assigned to the training and validation groups at a ratio of 7:3. Clinicopathologic and ultrasound (US) characteristics of both primary tumors and LNs were used to develop corresponding prediction models, and a nomogram integrating clinicopathologic and US predictors was generated to predict the axillary response to NAC.

Results

Axillary pathological complete response (pCR) was achieved in 47.79% of the patients. The expression of estrogen receptor, human epidermal growth factor receptor -2, Ki-67 score, and clinical nodal stage were independent predictors for nodal response to NAC. Location and radiological response of primary tumors, cortical thickness and shape of LNs on US were also significantly associated with nodal pCR. In the validation cohort, the discrimination of US model (area under the curve [AUC], 0.76) was superior to clinicopathologic model (AUC, 0.68); the combined model (AUC, 0.85) demonstrates strong discriminatory power in predicting nodal pCR. Calibration curves of the nomogram based on the combined model demonstrated that substantial agreement can be observed between the predictions and observations. This nomogram showed a false-negative rates of 16.67% in all patients and 10.53% in patients with triple negative breast cancer.

Conclusion

Nomogram incorporating routine clinicopathologic and US characteristics can predict nodal pCR and represents a tool to aid in treatment decisions for the axilla after NAC in breast cancer patients.

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来源期刊
Clinical breast cancer
Clinical breast cancer 医学-肿瘤学
CiteScore
5.40
自引率
3.20%
发文量
174
审稿时长
48 days
期刊介绍: Clinical Breast Cancer is a peer-reviewed bimonthly journal that publishes original articles describing various aspects of clinical and translational research of breast cancer. Clinical Breast Cancer is devoted to articles on detection, diagnosis, prevention, and treatment of breast cancer. The main emphasis is on recent scientific developments in all areas related to breast cancer. Specific areas of interest include clinical research reports from various therapeutic modalities, cancer genetics, drug sensitivity and resistance, novel imaging, tumor genomics, biomarkers, and chemoprevention strategies.
期刊最新文献
Editorial Board Table of Contents Clinical and Imaging Features Associated With Malignant Focal Nonmass Enhancement on Breast MRI. Real-World Outcomes of Pyrotinib-Based Therapy for HER2-Positive Breast Cancer With Brain Metastases: A Multicentre, Retrospective Analysis. Another Biosignature for Ductal Carcinoma In Situ-Have We Moved the Needle?
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