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Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis

Oncotype DX is a commercial assay frequently used for making chemotherapy decisions in estrogen receptor (ER)-positive breast cancers. The result is reported as a recurrence score ranging from 0 to 100, divided into low-risk (<18), intermediate-risk (18–30), and high-risk (≥31) categories. Our pi...

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Autores principales: Klein, Molly E, Dabbs, David J, Shuai, Yongli, Brufsky, Adam M, Jankowitz, Rachel, Puhalla, Shannon L, Bhargava, Rohit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647116/
https://www.ncbi.nlm.nih.gov/pubmed/23503643
http://dx.doi.org/10.1038/modpathol.2013.36
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author Klein, Molly E
Dabbs, David J
Shuai, Yongli
Brufsky, Adam M
Jankowitz, Rachel
Puhalla, Shannon L
Bhargava, Rohit
author_facet Klein, Molly E
Dabbs, David J
Shuai, Yongli
Brufsky, Adam M
Jankowitz, Rachel
Puhalla, Shannon L
Bhargava, Rohit
author_sort Klein, Molly E
collection PubMed
description Oncotype DX is a commercial assay frequently used for making chemotherapy decisions in estrogen receptor (ER)-positive breast cancers. The result is reported as a recurrence score ranging from 0 to 100, divided into low-risk (<18), intermediate-risk (18–30), and high-risk (≥31) categories. Our pilot study showed that recurrence score can be predicted by an equation incorporating standard morphoimmunohistologic variables (referred to as original Magee equation). Using a data set of 817 cases, we formulated three additional equations (referred to as new Magee equations 1, 2, and 3) to predict the recurrence score category for an independent set of 255 cases. The concordance between the risk category of Oncotype DX and our equations was 54.3%, 55.8%, 59.4%, and 54.4% for original Magee equation, new Magee equations 1, 2, and 3, respectively. When the intermediate category was eliminated, the concordance increased to 96.9%, 100%, 98.6%, and 98.7% for original Magee equation, new Magee equations 1, 2, and 3, respectively. Even when the estimated recurrence score fell in the intermediate category with any of the equations, the actual recurrence score was either intermediate or low in more than 80% of the cases. Any of the four equations can be used to estimate the recurrence score depending on available data. If the estimated recurrence score is clearly high or low, the oncologists should not expect a dramatically different result from Oncotype DX, and the Oncotype DX test may not be needed. Conversely, an Oncotype DX result that is dramatically different from what is expected based on standard morphoimmunohistologic variables should be thoroughly investigated.
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spelling pubmed-36471162013-05-10 Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis Klein, Molly E Dabbs, David J Shuai, Yongli Brufsky, Adam M Jankowitz, Rachel Puhalla, Shannon L Bhargava, Rohit Mod Pathol Original Article Oncotype DX is a commercial assay frequently used for making chemotherapy decisions in estrogen receptor (ER)-positive breast cancers. The result is reported as a recurrence score ranging from 0 to 100, divided into low-risk (<18), intermediate-risk (18–30), and high-risk (≥31) categories. Our pilot study showed that recurrence score can be predicted by an equation incorporating standard morphoimmunohistologic variables (referred to as original Magee equation). Using a data set of 817 cases, we formulated three additional equations (referred to as new Magee equations 1, 2, and 3) to predict the recurrence score category for an independent set of 255 cases. The concordance between the risk category of Oncotype DX and our equations was 54.3%, 55.8%, 59.4%, and 54.4% for original Magee equation, new Magee equations 1, 2, and 3, respectively. When the intermediate category was eliminated, the concordance increased to 96.9%, 100%, 98.6%, and 98.7% for original Magee equation, new Magee equations 1, 2, and 3, respectively. Even when the estimated recurrence score fell in the intermediate category with any of the equations, the actual recurrence score was either intermediate or low in more than 80% of the cases. Any of the four equations can be used to estimate the recurrence score depending on available data. If the estimated recurrence score is clearly high or low, the oncologists should not expect a dramatically different result from Oncotype DX, and the Oncotype DX test may not be needed. Conversely, an Oncotype DX result that is dramatically different from what is expected based on standard morphoimmunohistologic variables should be thoroughly investigated. Nature Publishing Group 2013-05 2013-03-15 /pmc/articles/PMC3647116/ /pubmed/23503643 http://dx.doi.org/10.1038/modpathol.2013.36 Text en Copyright © 2013 United States and Canadian Academy of Pathology, Inc. http://creativecommons.org/licenses/by-nc-nd/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/
spellingShingle Original Article
Klein, Molly E
Dabbs, David J
Shuai, Yongli
Brufsky, Adam M
Jankowitz, Rachel
Puhalla, Shannon L
Bhargava, Rohit
Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title_full Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title_fullStr Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title_full_unstemmed Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title_short Prediction of the Oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis
title_sort prediction of the oncotype dx recurrence score: use of pathology-generated equations derived by linear regression analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647116/
https://www.ncbi.nlm.nih.gov/pubmed/23503643
http://dx.doi.org/10.1038/modpathol.2013.36
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