MRI Volume Changes of Axillary Lymph Nodes as Predictor of Pathologic Complete Responses to Neoadjuvant Chemotherapy in Breast Cancer.
Adult
Antineoplastic Combined Chemotherapy Protocols
/ therapeutic use
Axilla
Breast
/ pathology
Breast Neoplasms
/ diagnosis
Chemotherapy, Adjuvant
/ methods
Clinical Trials, Phase II as Topic
Datasets as Topic
Female
Humans
Lymphatic Metastasis
Magnetic Resonance Imaging
Mastectomy
Middle Aged
Neoadjuvant Therapy
Predictive Value of Tests
Prognosis
Randomized Controlled Trials as Topic
Retrospective Studies
Sentinel Lymph Node
/ diagnostic imaging
Treatment Outcome
Tumor Burden
/ drug effects
Breast tumor volume
Dynamic contrast-enhanced MRI
Magnetic resonance imaging
Molecular subtypes
Sentinel lymph node biopsy
Journal
Clinical breast cancer
ISSN: 1938-0666
Titre abrégé: Clin Breast Cancer
Pays: United States
ID NLM: 100898731
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
17
01
2019
revised:
24
05
2019
accepted:
13
06
2019
pubmed:
23
7
2019
medline:
30
3
2021
entrez:
23
7
2019
Statut:
ppublish
Résumé
Longitudinal monitoring of breast tumor volume over the course of chemotherapy is informative of pathologic response. This study aims to determine whether axillary lymph node (aLN) volume by magnetic resonance imaging (MRI) could augment the prediction accuracy of treatment response to neoadjuvant chemotherapy (NAC). Level-2a curated data from the I-SPY-1 TRIAL (2002-2006) were used. Patients had stage 2 or 3 breast cancer. MRI was acquired pre-, during, and post-NAC. A subset with visible aLNs on MRI was identified (N = 132). Prediction of pathologic complete response (PCR) was made using breast tumor volume changes, nodal volume changes, and combined breast tumor and nodal volume changes with sub-stratification with and without large lymph nodes (3 mL or ∼1.79 cm diameter cutoff). Receiver operating characteristic curve analysis was used to quantify prediction performance. The rate of change of aLN and breast tumor volume were informative of pathologic response, with prediction being most informative early in treatment (area under the curve (AUC), 0.57-0.87) compared with later in treatment (AUC, 0.50-0.75). Larger aLN volume was associated with hormone receptor negativity, with the largest nodal volume for triple negative subtypes. Sub-stratification by node size improved predictive performance, with the best predictive model for large nodes having AUC of 0.87. aLN MRI offers clinically relevant information and has the potential to predict treatment response to NAC in patients with breast cancer.
Identifiants
pubmed: 31327729
pii: S1526-8209(19)30037-0
doi: 10.1016/j.clbc.2019.06.006
pii:
doi:
Types de publication
Evaluation Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
68-79.e1Informations de copyright
Copyright © 2019 Elsevier Inc. All rights reserved.