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Axillary ultrasound after neoadjuvant therapy reduces the false-negative rate of sentinel lymph node biopsy in patients with cytologically node-positive breast cancer

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Abstract

Objectives

This study aimed to determine whether post-neoadjuvant therapy (NAT) axillary ultrasound (AUS) could reduce the false-negative rate (FNR) of sentinel lymph node biopsy (SLNB). We also performed subgroup analyses to identify the appropriate patient for SLNB.

Methods

A total of 220 patients with cytologically proven axillary node-positive breast cancer who underwent both SLNB and axillary lymph node dissection (ALND) after NAT were included. We calculated the FNR of SLNB. In the case of post-NAT AUS results available, AUS was classified as negative or positive. Then the FNR of post-NAT AUS combined with SLNB was evaluated. Subgroup analyses based on the number of sentinel lymph nodes removed, molecular subtypes, and the clinical N stage were also performed.

Results

The overall axillary lymph node pathological complete response rate was 45.5% (100/220). The FNR of SLNB alone was 15.8% (95%CI: 9.2 to 22.5%). Post-NAT AUS results were available for 181 patients. When combined negative post-NAT AUS results and SLNB, the FNR was reduced to 7.5% (95%CI: 2.4 to 12.7%). Subgroup analyses of the FNR for SLNB alone and negative post-NAT AUS combined with SLNB were shown as follows: in cases patients with less than three sentinel lymph nodes (SLNs) and at least three SLNs removed, the FNR was decreased from 24.5 to 13.2%, and 9.0 to 5.0%, respectively. The FNR was decreased from 20.8 to 10.5% in HR+/HER2+subgroup, 21.4 to 16.7% in HR−/HER2+subgroup, 15.9 to 7.0% in HR+/HER2− subgroup, and 0% in HR−/HER2− subgroup, respectively. For cN1 patients, the FNR was decreased from 18.1 to 12.1% while 17.1 to 3.6% for cN2 patients and 0% for cN3 patients.

Conclusion

Using negative post-NAT AUS may help to decrease the FNR and improve patient selection for SLNB.

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Data availability

Due to the privacy of patients, the data related to patients cannot be available for public access but can be obtained from the corresponding author (liangchanghong@gdph.org.cn) on reasonable request approved by the institutional review board of all enrolled centers.

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Funding

This work was funded by the Key-Area Research and Development Program of Guangdong Province (No.2021B0101420006); National Natural Science Foundation of China (No.82071892, 82271941,82272088, 82171920); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No.2022B1212010011); the National Science Foundation for Young Scientists of China (No.82102019, 82001986); Project Funded by China Postdoctoral Science Foundation (No.2020M682643, 2021M700897); High-level Hospital Construction Project (DFJH201805, DFJHBF202105).

Author information

Author notes

  1. Yu Liu, Ying Wang, and Senwen Feng have contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China

    Yu Liu, Zeyan Xu, Xiaomei Huang, Pinxiong Li, Lei Wu, Chunling Liu, Changhong Liang & Zaiyi Liu

  2. Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China

    Yu Liu, Zeyan Xu, Xiaomei Huang, Pinxiong Li, Lei Wu, Chunling Liu, Changhong Liang & Zaiyi Liu

  3. The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China

    Yu Liu & Changhong Liang

  4. Department of Medical Ultrasonics, The First Affiliated Hospital of Guangzhou Medical University, 151 Yanjiang West Road, Guangzhou, 510120, China

    Ying Wang

  5. Department of General Surgery, Guangdong Second Traditional Chinese Medicine Hospital, Guangzhou, 510095, China

    Senwen Feng

  6. Department of Ultrasound, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou, 510080, China

    Mengxia Yao

  7. Department of Radiology, School of Medicine, Guangzhou First People’s Hospital, South China University of Technology, 1 Panfu Road, Guangzhou, 510180, China

    Xin Chen

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  1. Yu Liu
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Contributions

YL, YW, SF: conceptualization; YL, SF, ZX, XH, MY: methodology; YL, XH, ZX, CL: verification of data; CL, ZL, YW: investigation; MY, CL, XC,PL: visualization; MY, LW, CL: supervision; YL, SF: writing—original draft; CL, ZL, YW, ZX, XH: writing—review & editing.

Corresponding authors

Correspondence to Changhong Liang or Zaiyi Liu.

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Liu, Y., Wang, Y., Feng, S. et al. Axillary ultrasound after neoadjuvant therapy reduces the false-negative rate of sentinel lymph node biopsy in patients with cytologically node-positive breast cancer. Breast Cancer Res Treat 197, 515–523 (2023). https://doi.org/10.1007/s10549-022-06817-8

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