Nodal Response to Neoadjuvant Chemotherapy Predicts Receipt of Radiation Therapy after Breast Cancer Diagnosis.
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.
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https://hdl.handle.net/10161/19534Published Version (Please cite this version)
10.1016/j.ijrobp.2019.10.039Publication 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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Show full item recordScholars@Duke
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
Jeremy M Force
Assistant Professor of Medicine
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
Eun-Sil Shelley Hwang
Mary and Deryl Hart Distinguished Professor of Surgery, in the School of Medicine
Terry Hyslop
Adjunct Professor in the Department of Biostatistics & Bioinformatics
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
Laura Horst Rosenberger
Associate Professor of Surgery
Gita Suneja
Associate Professor of Radiation Oncology
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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