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新辅助化疗后MRI完全缓解且乳腺钼靶有残留钙化的乳腺癌患者个体化精准手术预测模型

Prediction model for individualized precision surgery in breast cancer patients with complete response on MRI and residual calcifications on mammography after neoadjuvant chemotherapy.

作者信息

Kwon Mi-Ri, Ko Eun Young, Lee Jeong Eon, Han Boo-Kyung, Ko Eun Sook, Choi Ji Soo, Kim Haejung, Kim Myoung Kyoung, Yu Jonghan, Lee Hyunwoo, Youn Inyoung

机构信息

Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.

Department of Radiology and Center for Imaging Science, Samsung Medical Center,, Sungkyunkwan University School of Medicine, Seoul, Korea.

出版信息

Breast Cancer. 2025 Jan;32(1):109-119. doi: 10.1007/s12282-024-01638-7. Epub 2024 Sep 30.

Abstract

BACKGROUND

Identifying whether there is residual carcinoma in remaining suspicious calcifications after neoadjuvant chemotherapy (NAC) in breast cancer patients can provide crucial information for surgeons in determining the most appropriate surgical approach. Therefore, we investigated factors predicting calcifications without residual carcinoma (ypCalc_0) or with residual carcinoma (ypCalc_ca) and aimed to develop a prediction model for patients exhibiting residual suspicious calcifications on mammography but complete response on MRI after NAC.

METHODS

This retrospective study included breast cancer patients undergoing NAC, showing residual suspicious mammographic calcifications but complete response on MRI between January 2019 and December 2020 (development set) and between January 2021 and December 2022 (validation set). Multivariable logistic regression analysis identified significant factors associated with ypCalc_0. The prediction model, developed using a decision tree and factors from logistic regression analysis, was validated in the validation set.

RESULTS

The development set included 134 women (mean age, 50.6 years; 91 with ypCalc_0 and 43 with ypCalc_ca) and validation set included 146 women (mean age, 51.0 years; 108 with ypCalc_0 and 38 with ypCalc_ca). Molecular subtype (P = .0002) and high Ki-67 (P = .02) emerged as significant independent factors associated with ypCalc_0 in the development set. The prediction model, incorporating hormone receptor (HR)-/human epidermal growth factor receptor 2 (HER2)+ with high Ki-67 as ypCalc_0 predictors, and HR+/HER2- cancers or HR+/HER2+ or triple-negative (TN) cancers with low Ki-67, as ypCalc_ca predictors, achieved an area under receiver operating characteristic curve of 0.844 (95% CI 0.774-0.914) in the validation set.

CONCLUSION

Minimized surgery may be considered for managing residual calcifications in HR-/HER2+ with high Ki-67 cancers, while complete excision is recommended for HR+/HER2- breast cancers or for HR+/HER2+or TN breast cancers with low Ki-67.

摘要

背景

确定乳腺癌患者新辅助化疗(NAC)后剩余可疑钙化灶中是否存在残留癌,可为外科医生确定最合适的手术方式提供关键信息。因此,我们研究了预测无残留癌(ypCalc_0)或有残留癌(ypCalc_ca)的钙化灶的因素,旨在为NAC后乳腺钼靶检查显示有残留可疑钙化灶但MRI检查呈完全缓解的患者建立预测模型。

方法

这项回顾性研究纳入了2019年1月至2020年12月(开发集)以及2021年1月至2022年12月(验证集)期间接受NAC、乳腺钼靶检查有残留可疑钙化灶但MRI检查呈完全缓解的乳腺癌患者。多变量逻辑回归分析确定了与ypCalc_0相关的显著因素。使用决策树和逻辑回归分析中的因素开发的预测模型在验证集中进行了验证。

结果

开发集包括134名女性(平均年龄50.6岁;91例ypCalc_0,43例ypCalc_ca),验证集包括146名女性(平均年龄51.0岁;108例ypCalc_0,38例ypCalc_ca)。分子亚型(P = 0.0002)和高Ki-67(P = 0.02)在开发集中成为与ypCalc_0相关的显著独立因素。该预测模型将激素受体(HR)-/人表皮生长因子受体2(HER2)+且Ki-67高作为ypCalc_0预测因子,HR+/HER2-癌症或HR+/HER2+或三阴性(TN)癌症且Ki-67低作为ypCalc_ca预测因子,在验证集中的受试者工作特征曲线下面积为0.844(95%CI 0.774 - 0.914)。

结论

对于HR-/HER2+且Ki-67高的癌症患者,处理残留钙化灶时可考虑进行最小化手术,而对于HR+/HER2-乳腺癌或HR+/HER2+或TN乳腺癌且Ki-67低的患者,建议进行完整切除。

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