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Imaging Biomarkers as Predictors for Breast Cancer Death

BACKGROUND: To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes. METHODS: Using a prospective cohor...

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Autores principales: Wu, Wendy Yi-Ying, Tabar, Laszlo, Tot, Tibor, Fann, Ching-Yuan, Yen, Amy Ming-Fang, Chen, Sam Li-Sheng, Chiu, Sherry Yueh-Hsia, Ku, May Mei-Sheng, Hsu, Chen-Yang, Beckmann, Kerri R., Smith, Robert A., Duffy, Stephen W., Chen, Hsiu-Hsi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481030/
https://www.ncbi.nlm.nih.gov/pubmed/31093281
http://dx.doi.org/10.1155/2019/2087983
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author Wu, Wendy Yi-Ying
Tabar, Laszlo
Tot, Tibor
Fann, Ching-Yuan
Yen, Amy Ming-Fang
Chen, Sam Li-Sheng
Chiu, Sherry Yueh-Hsia
Ku, May Mei-Sheng
Hsu, Chen-Yang
Beckmann, Kerri R.
Smith, Robert A.
Duffy, Stephen W.
Chen, Hsiu-Hsi
author_facet Wu, Wendy Yi-Ying
Tabar, Laszlo
Tot, Tibor
Fann, Ching-Yuan
Yen, Amy Ming-Fang
Chen, Sam Li-Sheng
Chiu, Sherry Yueh-Hsia
Ku, May Mei-Sheng
Hsu, Chen-Yang
Beckmann, Kerri R.
Smith, Robert A.
Duffy, Stephen W.
Chen, Hsiu-Hsi
author_sort Wu, Wendy Yi-Ying
collection PubMed
description BACKGROUND: To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes. METHODS: Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010. RESULTS: Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death. CONCLUSION: Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.
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spelling pubmed-64810302019-05-15 Imaging Biomarkers as Predictors for Breast Cancer Death Wu, Wendy Yi-Ying Tabar, Laszlo Tot, Tibor Fann, Ching-Yuan Yen, Amy Ming-Fang Chen, Sam Li-Sheng Chiu, Sherry Yueh-Hsia Ku, May Mei-Sheng Hsu, Chen-Yang Beckmann, Kerri R. Smith, Robert A. Duffy, Stephen W. Chen, Hsiu-Hsi J Oncol Research Article BACKGROUND: To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes. METHODS: Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010. RESULTS: Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death. CONCLUSION: Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients. Hindawi 2019-04-10 /pmc/articles/PMC6481030/ /pubmed/31093281 http://dx.doi.org/10.1155/2019/2087983 Text en Copyright © 2019 Wendy Yi-Ying Wu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wu, Wendy Yi-Ying
Tabar, Laszlo
Tot, Tibor
Fann, Ching-Yuan
Yen, Amy Ming-Fang
Chen, Sam Li-Sheng
Chiu, Sherry Yueh-Hsia
Ku, May Mei-Sheng
Hsu, Chen-Yang
Beckmann, Kerri R.
Smith, Robert A.
Duffy, Stephen W.
Chen, Hsiu-Hsi
Imaging Biomarkers as Predictors for Breast Cancer Death
title Imaging Biomarkers as Predictors for Breast Cancer Death
title_full Imaging Biomarkers as Predictors for Breast Cancer Death
title_fullStr Imaging Biomarkers as Predictors for Breast Cancer Death
title_full_unstemmed Imaging Biomarkers as Predictors for Breast Cancer Death
title_short Imaging Biomarkers as Predictors for Breast Cancer Death
title_sort imaging biomarkers as predictors for breast cancer death
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481030/
https://www.ncbi.nlm.nih.gov/pubmed/31093281
http://dx.doi.org/10.1155/2019/2087983
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