Development and validation of a combined ultrasound-pathology model to predict axillary status after neoadjuvant systemic therapy in breast cancer.

IF 3.2 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
International Journal of Medical Sciences Pub Date : 2024-10-21 eCollection Date: 2024-01-01 DOI:10.7150/ijms.101855
Wenjie Shi, Jinzhi He, Xuan Li, Hailing Zha, Rui Chen, Lu Xu, Xiaoming Zha, Jue Wang
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引用次数: 0

Abstract

Background: This study aimed to develop a combined ultrasound (US)-pathology model to predict the axillary status more accurately after NST in breast cancer. Methods: This retrospective study included breast cancer patients who received NST at the First Affiliated Hospital of Nanjing Medical University from 2015 to 2022. Clinical, US, and pathological data were collected. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of axillary pathological complete response (pCR). The model was developed using the predictors and validated. Results: A total of 657 patients were enrolled in this study. Two multivariate logistic analyses were performed before and after the operation. The results showed that the clinical lymph nodes, ER status, HER2 status, chemotherapy response of primary tumor, hilum structure of axillary lymph nodes (ALNs) after NST, blood flow of ALNs after NST, vascular invasion, pathological size, and Miller-Payne grade (all p < 0.05) were independent predictors of axillary pCR. The US-based and combined US-pathology models were developed based on preoperative and postoperative information. The two models had an area under the receiver operating characteristic curve (AUC) of 0.821 and 0.883, respectively, which was significantly higher than that of the fine-needle aspiration model (AUC: 0.735). Conclusion: In this study, based on the US-based model, a combined model incorporating the characteristics of ALNs under US and breast pathology was developed and validated to predict axillary pCR.

开发并验证用于预测乳腺癌新辅助系统治疗后腋窝状态的超声-病理联合模型。
研究背景本研究旨在开发一种超声(US)-病理学联合模型,以更准确地预测乳腺癌 NST 后的腋窝状态。研究方法这项回顾性研究纳入了2015年至2022年在南京医科大学第一附属医院接受NST治疗的乳腺癌患者。收集了临床、美国和病理数据。进行单变量和多变量逻辑回归分析,以确定腋窝病理完全反应(pCR)的独立预测因素。利用这些预测因素建立了模型并进行了验证。结果本研究共纳入 657 例患者。在手术前后进行了两次多变量逻辑分析。结果显示,临床淋巴结、ER状态、HER2状态、原发肿瘤的化疗反应、NST后腋窝淋巴结(ALNs)的蒂部结构、NST后腋窝淋巴结的血流、血管侵犯、病理大小和Miller-Payne分级(P均<0.05)是腋窝pCR的独立预测因素。基于US的模型和US-病理联合模型是根据术前和术后信息建立的。这两个模型的接收者操作特征曲线下面积(AUC)分别为 0.821 和 0.883,明显高于细针穿刺模型(AUC:0.735)。结论本研究在基于US的模型的基础上,结合US和乳腺病理检查下ALN的特征,建立并验证了预测腋窝pCR的联合模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Medical Sciences
International Journal of Medical Sciences MEDICINE, GENERAL & INTERNAL-
CiteScore
7.20
自引率
0.00%
发文量
185
审稿时长
2.7 months
期刊介绍: Original research papers, reviews, and short research communications in any medical related area can be submitted to the Journal on the understanding that the work has not been published previously in whole or part and is not under consideration for publication elsewhere. Manuscripts in basic science and clinical medicine are both considered. There is no restriction on the length of research papers and reviews, although authors are encouraged to be concise. Short research communication is limited to be under 2500 words.
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