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Nodal Response to Neoadjuvant Chemotherapy Predicts Receipt of Radiation Therapy after Breast Cancer Diagnosis.

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Date
2019-10-31
Authors
Fayanju, Oluwadamilola M
Ren, Yi
Suneja, Gita
Thomas, Samantha M
Greenup, Rachel A
Plichta, Jennifer K
Rosenberger, Laura H
Force, Jeremy
Hyslop, Terry
Hwang, E Shelley
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Abstract
BACKGROUND:Pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is associated with improved overall survival (OS) in breast-cancer patients, but it is unclear how post-NACT response influences radiotherapy administration in patients presenting with node-positive disease. We sought to determine whether nodal pCR is associated with likelihood of receiving nodal radiation and whether radiotherapy among patients experiencing nodal pCR is associated with improved OS. METHODS:cN1 female breast cancer patients diagnosed 2010-2015 who were ypN0 (i.e., nodal pCR, n=12,341) or ypN1 (i.e., residual disease, n=13,668) post-NACT were identified in the National Cancer Database. Multivariate logistic regression was used to identify factors associated with receiving radiotherapy. Cox proportional hazards modeling was used to estimate the association between radiotherapy and adjusted OS. RESULTS:26,009 patients were included. 43.9% (n=5,423) of ypN0 and 55.3% (n=7,556) of ypN1 patients received nodal radiation. Rates of nodal radiation remained the same over time among ypN0 patients (trend test p=0.29) but increased among ypN1 patients from 49% in 2010 to 59% in 2015 (trend test p<0.001). After adjusting for covariates, nodal pCR (vs no stage change) was associated with decreased likelihood of nodal radiation after mastectomy (∼20% decrease) and lumpectomy (∼30% decrease, both p<0.01). After mastectomy, nodal (vs no) radiation conferred no significant survival benefit in ypN0 patients but approached significance for ypN1 patients (hazard ratio [HR] 0.83, 95% CI 0.69-0.99, p=0.04, overall p-value=0.11). After lumpectomy, nodal radiation was associated with improved adjusted OS for ypN0 (HR 0.38, 95% CI 0.22-0.66) and ypN1 patients (HR 0.44, 95% CI 0.30-0.66, both p<0.001), but this improvement was not significantly greater than that associated with breast-only radiation. CONCLUSIONS:ypN0 patients were less likely to receive nodal radiation than ypN1 patients, suggesting that selective omission already occurs and, in the context of limited survival data, could potentially be appropriate for select patients.
Type
Journal article
Subject
axilla
breast cancer
lymph nodes
neoadjuvant chemotherapy
pathologic complete response
radiation
Permalink
https://hdl.handle.net/10161/19534
Published Version (Please cite this version)
10.1016/j.ijrobp.2019.10.039
Publication Info
Fayanju, Oluwadamilola M; Ren, Yi; Suneja, Gita; Thomas, Samantha M; Greenup, Rachel A; Plichta, Jennifer K; ... Hwang, E Shelley (2019). Nodal Response to Neoadjuvant Chemotherapy Predicts Receipt of Radiation Therapy after Breast Cancer Diagnosis. International journal of radiation oncology, biology, physics. 10.1016/j.ijrobp.2019.10.039. Retrieved from https://hdl.handle.net/10161/19534.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Fayanju

Oluwadamilola Motunrayo Fayanju

Associate Professor of Surgery
Dr. Fayanju is an Associate Professor of Surgery and Population Health Sciences in the Duke University School of Medicine, Associate Director for Disparities & Value in Healthcare with Duke Forge (the university’s center for actionable data science: https://forge.duke.edu/oluwadamilola-fayanju-md-ma-mphs), and Director of the Durham VA Breast Clinic. She received her undergraduate degree in History and
Force

Jeremy M Force

Assistant Professor of Medicine
Greenup

Rachel Adams Greenup

Associate Professor of Surgery
Dr. Greenup is an Associate Professor of Surgery and Population Health Sciences at the Duke School of Medicine and Duke Cancer Institute. She is the founder and co-director of the Duke Breast Cancer Outcomes Research Group, and Core Faculty for the Duke Margolis Center for Health Policy. She earned her undergraduate degrees in Zoology and Psychology at the University of Wisconsin, where she later completed a Masters in Public Health. She attended the Medical College of Wisconsin for M
Hwang

Eun-Sil Shelley Hwang

Mary and Deryl Hart Distinguished Professor of Surgery, in the School of Medicine
Hyslop

Terry Hyslop

Adjunct Professor in the Department of Biostatistics & Bioinformatics
Plichta

Jennifer K Plichta

Associate Professor of Surgery
Dr. Jennifer Plichta is an Associate Professor of Surgery & Population Health Sciences at Duke University. She serves as the Director of the Breast Risk Assessment Clinic in the Duke Cancer Institute, where she cares for patients with breast cancer, benign breast problems, and those with an increased risk of breast cancer. Her clinical interests include establishing routine breast cancer risk assessment for women and creating personalized management strategies for those found to be &ldquo
Rosenberger

Laura Horst Rosenberger

Associate Professor of Surgery
Suneja

Gita Suneja

Associate Professor of Radiation Oncology
Thomas

Samantha Thomas

Biostatistician, Principal
Samantha is the manager of the Duke Cancer Institute (DCI) Biostatistics Shared Resource. Collaboratively, she primarily works with physicians in DCI, specifically in research of Endocrine Neoplasia and Breast Cancer. She is also the director of the Biostatistics, Epidemiology, Research, and Design Methods (BERD) Core Training and Internship Program (BCTIP). Her professional experience involves study design, analysis, and reporting of clinical trials and observational studies. Her specific areas
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