Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26

Abstract The skyrocketing cost of health‐care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX® (ODX) testing. This study is...

Full description

Bibliographic Details
Main Authors: Bradley M. Turner, Mary Ann Gimenez‐Sanders, Armen Soukiazian, Andrea C. Breaux, Kristin Skinner, Michelle Shayne, Nyrie Soukiazian, Marilyn Ling, David G. Hicks
Format: Article
Language:English
Published: Wiley 2019-08-01
Series:Cancer Medicine
Subjects:
Online Access:https://doi.org/10.1002/cam4.2323
id doaj-b1be917011db4b41aedf1fbf7d9e2b92
record_format Article
spelling doaj-b1be917011db4b41aedf1fbf7d9e2b922020-11-24T23:53:49ZengWileyCancer Medicine2045-76342019-08-01894176418810.1002/cam4.2323Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26Bradley M. Turner0Mary Ann Gimenez‐Sanders1Armen Soukiazian2Andrea C. Breaux3Kristin Skinner4Michelle Shayne5Nyrie Soukiazian6Marilyn Ling7David G. Hicks8Department of Pathology and Laboratory Medicine University of Rochester Rochester New YorkDepartment of Pathology and Laboratory Medicine University of Louisville Louisville KentuckyUniversity of Rochester Rochester New YorkDepartment of Pathology and Laboratory Medicine University of Louisville Louisville KentuckyDepartment of Surgery University of Rochester Medical Center Rochester New YorkDepartment of Medical Oncology University of Rochester Rochester New YorkDrexel University College of Medicine Graduate School of Biomedical and Professional Studies Philadelphia PennsylvaniaDepartment of Radiation Oncology University of Rochester Rochester New YorkDepartment of Pathology and Laboratory Medicine University of Rochester Medical Center Rochester New YorkAbstract The skyrocketing cost of health‐care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX® (ODX) testing. This study is a multi‐institutional validation of that algorithmic model in 620 additional estrogen receptor positive breast cancer cases, with outcome data on 310 cases, named in this study as the Rochester Modified Magee algorithm (RoMMa). RoMMa correctly predicted 85% (140/164) and 100% (17/17) of cases to have a low‐ or high‐risk ODX recurrence score, respectively, consistent with the original publication. Applying our own risk stratification criteria, in patients who received appropriate hormonal therapy, only one of the 45 (2.0%) patients classified as low risk by our original algorithm have been associated with a breast cancer recurrence over 5‐10 years of follow‐up. Eight of 116 (7.0%) patients classified as low risk by ODX have been associated with a breast cancer recurrence with up to 11 years of follow‐up. In addition, 524 of 537 (98%) cases from our total population (n = 903) with an average modified Magee score ≤18 had an ODX recurrence score <26. Patients with an average modified Magee score ≤18 or >30 may not need to be sent out for ODX testing. By avoiding these cases sending out for ODX testing, the potential cost savings to the health‐care system in 2018 are estimated to have been over $100,000,000.https://doi.org/10.1002/cam4.2323algorithmER+ breast cancerOncotype DX®recurrenceRoMMa
collection DOAJ
language English
format Article
sources DOAJ
author Bradley M. Turner
Mary Ann Gimenez‐Sanders
Armen Soukiazian
Andrea C. Breaux
Kristin Skinner
Michelle Shayne
Nyrie Soukiazian
Marilyn Ling
David G. Hicks
spellingShingle Bradley M. Turner
Mary Ann Gimenez‐Sanders
Armen Soukiazian
Andrea C. Breaux
Kristin Skinner
Michelle Shayne
Nyrie Soukiazian
Marilyn Ling
David G. Hicks
Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
Cancer Medicine
algorithm
ER+ breast cancer
Oncotype DX®
recurrence
RoMMa
author_facet Bradley M. Turner
Mary Ann Gimenez‐Sanders
Armen Soukiazian
Andrea C. Breaux
Kristin Skinner
Michelle Shayne
Nyrie Soukiazian
Marilyn Ling
David G. Hicks
author_sort Bradley M. Turner
title Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
title_short Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
title_full Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
title_fullStr Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
title_full_unstemmed Risk stratification of ER‐positive breast cancer patients: A multi‐institutional validation and outcome study of the Rochester Modified Magee algorithm (RoMMa) and prediction of an Oncotype DX® recurrence score <26
title_sort risk stratification of er‐positive breast cancer patients: a multi‐institutional validation and outcome study of the rochester modified magee algorithm (romma) and prediction of an oncotype dx® recurrence score <26
publisher Wiley
series Cancer Medicine
issn 2045-7634
publishDate 2019-08-01
description Abstract The skyrocketing cost of health‐care demands that we question when to use multigene assay testing in the planning of treatment for breast cancer patients. A previously published algorithmic model gave recommendations for which cases to send out for Oncotype DX® (ODX) testing. This study is a multi‐institutional validation of that algorithmic model in 620 additional estrogen receptor positive breast cancer cases, with outcome data on 310 cases, named in this study as the Rochester Modified Magee algorithm (RoMMa). RoMMa correctly predicted 85% (140/164) and 100% (17/17) of cases to have a low‐ or high‐risk ODX recurrence score, respectively, consistent with the original publication. Applying our own risk stratification criteria, in patients who received appropriate hormonal therapy, only one of the 45 (2.0%) patients classified as low risk by our original algorithm have been associated with a breast cancer recurrence over 5‐10 years of follow‐up. Eight of 116 (7.0%) patients classified as low risk by ODX have been associated with a breast cancer recurrence with up to 11 years of follow‐up. In addition, 524 of 537 (98%) cases from our total population (n = 903) with an average modified Magee score ≤18 had an ODX recurrence score <26. Patients with an average modified Magee score ≤18 or >30 may not need to be sent out for ODX testing. By avoiding these cases sending out for ODX testing, the potential cost savings to the health‐care system in 2018 are estimated to have been over $100,000,000.
topic algorithm
ER+ breast cancer
Oncotype DX®
recurrence
RoMMa
url https://doi.org/10.1002/cam4.2323
work_keys_str_mv AT bradleymturner riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT maryanngimenezsanders riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT armensoukiazian riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT andreacbreaux riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT kristinskinner riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT michelleshayne riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT nyriesoukiazian riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT marilynling riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
AT davidghicks riskstratificationoferpositivebreastcancerpatientsamultiinstitutionalvalidationandoutcomestudyoftherochestermodifiedmageealgorithmrommaandpredictionofanoncotypedxrecurrencescore26
_version_ 1725468340238942208