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Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer

PURPOSE: High-performing imaging and predictive markers are warranted to minimize surgical overtreatment of the axilla in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT). Here we have investigated whether axillary ultrasound (AUS) could identify axillary lymph node (ALN) metast...

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Autores principales: Skarping, Ida, Förnvik, Daniel, Zackrisson, Sophia, Borgquist, Signe, Rydén, Lisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302508/
https://www.ncbi.nlm.nih.gov/pubmed/34120224
http://dx.doi.org/10.1007/s10549-021-06283-8
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author Skarping, Ida
Förnvik, Daniel
Zackrisson, Sophia
Borgquist, Signe
Rydén, Lisa
author_facet Skarping, Ida
Förnvik, Daniel
Zackrisson, Sophia
Borgquist, Signe
Rydén, Lisa
author_sort Skarping, Ida
collection PubMed
description PURPOSE: High-performing imaging and predictive markers are warranted to minimize surgical overtreatment of the axilla in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT). Here we have investigated whether axillary ultrasound (AUS) could identify axillary lymph node (ALN) metastasis (ALNM) pre-NACT and post-NACT for BC. The association of tumor, AUS features and mammographic density (MD) with axillary-pathological complete response (axillary-pCR) post-NACT was also assessed. METHODS: The NeoDense-study cohort (N = 202, NACT during 2014–2019), constituted a pre-NACT cohort, whereas patients whom had a cytology verified ALNM pre-NACT and an axillary dissection performed (N = 114) defined a post-NACT cohort. AUS characteristics were prospectively collected pre- and post-NACT. The diagnostic accuracy of AUS was evaluated and stratified by histological subtype and body mass index (BMI). Predictors of axillary-pCR were analyzed, including MD, using simple and multivariable logistic regression models. RESULTS: AUS demonstrated superior performance for prediction of ALNM pre-NACT in comparison to post-NACT, as reflected by the positive predictive value (PPV) 0.94 (95% CI 0.89–0.97) and PPV 0.76 (95% CI 0.62–0.87), respectively. We found no difference in AUS performance according to neither BMI nor histological subtype. Independent predictors of axillary-pCR were: premenopausal status, ER-negativity, HER2-overexpression, and high MD. CONCLUSION: Baseline AUS could, to a large extent, identify ALNM; however, post-NACT, AUS was insufficient to determine remaining ALNM. Thus, our results support the surgical staging of the axilla post-NACT. Baseline tumor biomarkers and patient characteristics were predictive of axillary-pCR. Larger, multicenter studies are needed to evaluate the performance of AUS post-NACT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-021-06283-8.
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spelling pubmed-83025082021-07-27 Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer Skarping, Ida Förnvik, Daniel Zackrisson, Sophia Borgquist, Signe Rydén, Lisa Breast Cancer Res Treat Clinical Trial PURPOSE: High-performing imaging and predictive markers are warranted to minimize surgical overtreatment of the axilla in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT). Here we have investigated whether axillary ultrasound (AUS) could identify axillary lymph node (ALN) metastasis (ALNM) pre-NACT and post-NACT for BC. The association of tumor, AUS features and mammographic density (MD) with axillary-pathological complete response (axillary-pCR) post-NACT was also assessed. METHODS: The NeoDense-study cohort (N = 202, NACT during 2014–2019), constituted a pre-NACT cohort, whereas patients whom had a cytology verified ALNM pre-NACT and an axillary dissection performed (N = 114) defined a post-NACT cohort. AUS characteristics were prospectively collected pre- and post-NACT. The diagnostic accuracy of AUS was evaluated and stratified by histological subtype and body mass index (BMI). Predictors of axillary-pCR were analyzed, including MD, using simple and multivariable logistic regression models. RESULTS: AUS demonstrated superior performance for prediction of ALNM pre-NACT in comparison to post-NACT, as reflected by the positive predictive value (PPV) 0.94 (95% CI 0.89–0.97) and PPV 0.76 (95% CI 0.62–0.87), respectively. We found no difference in AUS performance according to neither BMI nor histological subtype. Independent predictors of axillary-pCR were: premenopausal status, ER-negativity, HER2-overexpression, and high MD. CONCLUSION: Baseline AUS could, to a large extent, identify ALNM; however, post-NACT, AUS was insufficient to determine remaining ALNM. Thus, our results support the surgical staging of the axilla post-NACT. Baseline tumor biomarkers and patient characteristics were predictive of axillary-pCR. Larger, multicenter studies are needed to evaluate the performance of AUS post-NACT. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10549-021-06283-8. Springer US 2021-06-12 2021 /pmc/articles/PMC8302508/ /pubmed/34120224 http://dx.doi.org/10.1007/s10549-021-06283-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Clinical Trial
Skarping, Ida
Förnvik, Daniel
Zackrisson, Sophia
Borgquist, Signe
Rydén, Lisa
Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title_full Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title_fullStr Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title_full_unstemmed Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title_short Predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
title_sort predicting pathological axillary lymph node status with ultrasound following neoadjuvant therapy for breast cancer
topic Clinical Trial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8302508/
https://www.ncbi.nlm.nih.gov/pubmed/34120224
http://dx.doi.org/10.1007/s10549-021-06283-8
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