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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Main Authors:	Klein, Molly E, Dabbs, David J, Shuai, Yongli, Brufsky, Adam M, Jankowitz, Rachel, Puhalla, Shannon L, Bhargava, Rohit
Format:	Online
Language:	English
Published:	Nature Publishing Group 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647116/

id	pubmed-3647116
recordtype	oai_dc
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 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/
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Klein, Molly E Dabbs, David J Shuai, Yongli Brufsky, Adam M Jankowitz, Rachel Puhalla, Shannon L Bhargava, Rohit
spellingShingle	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
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
title	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_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_sort	prediction of the oncotype dx recurrence score: use of pathology-generated equations derived by linear regression analysis
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.
publisher	Nature Publishing Group
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3647116/
_version_	1611975836496297984

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

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