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Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema

Background: If we use only volumetry for measuring lymphedema, we could underdiagnose lymphedema with characteristics of biomechanical changes without definite volume change, especially in the medial forearm. Methods and Results: In total, 158 breast cancer patients participated in this study. Arm v...

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Autores principales: Yang, Eun Joo, Kim, Seoung Yeon, Lee, Woo Hyung, Lim, Jae-Young, Lee, Jaebong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104249/
https://www.ncbi.nlm.nih.gov/pubmed/29338541
http://dx.doi.org/10.1089/lrb.2017.0047
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author Yang, Eun Joo
Kim, Seoung Yeon
Lee, Woo Hyung
Lim, Jae-Young
Lee, Jaebong
author_facet Yang, Eun Joo
Kim, Seoung Yeon
Lee, Woo Hyung
Lim, Jae-Young
Lee, Jaebong
author_sort Yang, Eun Joo
collection PubMed
description Background: If we use only volumetry for measuring lymphedema, we could underdiagnose lymphedema with characteristics of biomechanical changes without definite volume change, especially in the medial forearm. Methods and Results: In total, 158 breast cancer patients participated in this study. Arm volume was measured by water displacement volumetry, and segmental volumes were calculated from circumferences by using the truncated cone method. Subcutaneous ultrasound echogenicities were assessed on the medial side of the upper arm and forearm of both arms and graded by subcutaneous echogenicity grade (SEG) and revised SEG (rSEG). The standards for diagnosing secondary lymphedema were according to the volume change and clinical stage. Sensitivity, specificity, receiver-operating characteristic (ROC) curve, and area under the curve (AUC) were used. Analysis of ROC curves yielded AUCs of 0.875–0.933 (p < 0.001). Volume differences in each segment were significantly different among the grades by SEG. The highest AUC was found for volume difference (AUC = 0.919, 95% confidence interval [CI] = 0.860–0.978) in the upper arm near the elbow; however, in the medial forearm, the highest AUC was found for rSEG (AUC = 0.948, 95% CI = 0.923–0.965 in the proximal forearm; AUC = 0.940, 95% CI = 0.923–0.965 in the distal forearm). Conclusions: Our findings support the use of SEG by ultrasound in the assessment of lymphedema, especially in the medial region of the forearm. Subcutaneous ultrasound echogenicities may improve the accuracy of diagnosis of lymphedema in the forearm.
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spelling pubmed-61042492018-08-22 Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema Yang, Eun Joo Kim, Seoung Yeon Lee, Woo Hyung Lim, Jae-Young Lee, Jaebong Lymphat Res Biol Original Articles Background: If we use only volumetry for measuring lymphedema, we could underdiagnose lymphedema with characteristics of biomechanical changes without definite volume change, especially in the medial forearm. Methods and Results: In total, 158 breast cancer patients participated in this study. Arm volume was measured by water displacement volumetry, and segmental volumes were calculated from circumferences by using the truncated cone method. Subcutaneous ultrasound echogenicities were assessed on the medial side of the upper arm and forearm of both arms and graded by subcutaneous echogenicity grade (SEG) and revised SEG (rSEG). The standards for diagnosing secondary lymphedema were according to the volume change and clinical stage. Sensitivity, specificity, receiver-operating characteristic (ROC) curve, and area under the curve (AUC) were used. Analysis of ROC curves yielded AUCs of 0.875–0.933 (p < 0.001). Volume differences in each segment were significantly different among the grades by SEG. The highest AUC was found for volume difference (AUC = 0.919, 95% confidence interval [CI] = 0.860–0.978) in the upper arm near the elbow; however, in the medial forearm, the highest AUC was found for rSEG (AUC = 0.948, 95% CI = 0.923–0.965 in the proximal forearm; AUC = 0.940, 95% CI = 0.923–0.965 in the distal forearm). Conclusions: Our findings support the use of SEG by ultrasound in the assessment of lymphedema, especially in the medial region of the forearm. Subcutaneous ultrasound echogenicities may improve the accuracy of diagnosis of lymphedema in the forearm. Mary Ann Liebert, Inc. 2018-08-01 2018-08-01 /pmc/articles/PMC6104249/ /pubmed/29338541 http://dx.doi.org/10.1089/lrb.2017.0047 Text en © Yang et al. 2018; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Original Articles
Yang, Eun Joo
Kim, Seoung Yeon
Lee, Woo Hyung
Lim, Jae-Young
Lee, Jaebong
Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title_full Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title_fullStr Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title_full_unstemmed Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title_short Diagnostic Accuracy of Clinical Measures Considering Segmental Tissue Composition and Volume Changes of Breast Cancer-Related Lymphedema
title_sort diagnostic accuracy of clinical measures considering segmental tissue composition and volume changes of breast cancer-related lymphedema
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6104249/
https://www.ncbi.nlm.nih.gov/pubmed/29338541
http://dx.doi.org/10.1089/lrb.2017.0047
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