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Intelligent Vacuum-Assisted Biopsy to Identify Breast Cancer Patients With Pathologic Complete Response (ypT0 and ypN0) After Neoadjuvant Systemic Treatment for Omission of Breast and Axillary Surgery

Authors :
André Pfob
Chris Sidey-Gibbons
Geraldine Rauch
Bettina Thomas
Benedikt Schaefgen
Sherko Kuemmel
Toralf Reimer
Markus Hahn
Marc Thill
Jens-Uwe Blohmer
John Hackmann
Wolfram Malter
Inga Bekes
Kay Friedrichs
Sebastian Wojcinski
Sylvie Joos
Stefan Paepke
Tom Degenhardt
Joachim Rom
Achim Rody
Marion van Mackelenbergh
Maggie Banys-Paluchowski
Regina Große
Mattea Reinisch
Maria Karsten
Michael Golatta
Joerg Heil
Source :
Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 40(17)
Publication Year :
2022

Abstract

PURPOSENeoadjuvant systemic treatment (NST) elicits a pathologic complete response in 40%-70% of women with breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, nonsurgical approaches, including imaging or vacuum-assisted biopsy (VAB), were not able to accurately identify patients without residual cancer in the breast or axilla. We evaluated the feasibility of a machine learning algorithm (intelligent VAB) to identify exceptional responders to NST.METHODSWe trained, tested, and validated a machine learning algorithm using patient, imaging, tumor, and VAB variables to detect residual cancer after NST (ypT+ or in situ or ypN+) before surgery. We used data from 318 women with cT1-3, cN0 or +, human epidermal growth factor receptor 2–positive, triple-negative, or high-proliferative Luminal B–like breast cancer who underwent VAB before surgery (ClinicalTrials.gov identifier: NCT02948764 , RESPONDER trial). We used 10-fold cross-validation to train and test the algorithm, which was then externally validated using data of an independent trial (ClinicalTrials.gov identifier: NCT02575612 ). We compared findings with the histopathologic evaluation of the surgical specimen. We considered false-negative rate (FNR) and specificity to be the main outcomes.RESULTSIn the development set (n = 318) and external validation set (n = 45), the intelligent VAB showed an FNR of 0.0%-5.2%, a specificity of 37.5%-40.0%, and an area under the receiver operating characteristic curve of 0.91-0.92 to detect residual cancer (ypT+ or in situ or ypN+) after NST. Spiegelhalter's Z confirmed a well-calibrated model ( z score –0.746, P = .228). FNR of the intelligent VAB was lower compared with imaging after NST, VAB alone, or combinations of both.CONCLUSIONAn intelligent VAB algorithm can reliably exclude residual cancer after NST. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials.

Details

ISSN :
15277755
Volume :
40
Issue :
17
Database :
OpenAIRE
Journal :
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Accession number :
edsair.doi.dedup.....ec617c40be5cbed3ff6861979126f41b