Combined pathologic‐genomic algorithm for early-stage breast cancer improves cost-effective use of the 21-gene recurrence score assay
The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories...
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          | Published in | Annals of oncology Vol. 29; no. 5; pp. 1280 - 1285 | 
|---|---|
| Main Authors | , , , , , , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        England
          Elsevier Ltd
    
        01.05.2018
     Oxford University Press  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0923-7534 1569-8041 1569-8041  | 
| DOI | 10.1093/annonc/mdy074 | 
Cover
| Abstract | The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic‐genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients.
A survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan–Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model’s risk groups.
A total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n=322) and the RS<18 low-risk group (3.4%, n=703), as well as between the AAMC high-risk group (22.8%, n=230) and the RS>30 high-risk group (23.0%, n=141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n=739) and 24.2% for the high-risk group (n=272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing.
AAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk. | 
    
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| AbstractList | Abstract
Background
The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic‐genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients.
Patients and methods
A survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan–Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model’s risk groups.
Results
A total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n = 322) and the RS < 18 low-risk group (3.4%, n = 703), as well as between the AAMC high-risk group (22.8%, n = 230) and the RS > 30 high-risk group (23.0%, n = 141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n = 739) and 24.2% for the high-risk group (n = 272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing.
Conclusions
AAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk. The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic-genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients. A survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan-Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model's risk groups. A total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n = 322) and the RS < 18 low-risk group (3.4%, n = 703), as well as between the AAMC high-risk group (22.8%, n = 230) and the RS > 30 high-risk group (23.0%, n = 141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n = 739) and 24.2% for the high-risk group (n = 272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing. AAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk. The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic-genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients.BackgroundThe 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic-genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients.A survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan-Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model's risk groups.Patients and methodsA survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan-Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model's risk groups.A total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n = 322) and the RS < 18 low-risk group (3.4%, n = 703), as well as between the AAMC high-risk group (22.8%, n = 230) and the RS > 30 high-risk group (23.0%, n = 141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n = 739) and 24.2% for the high-risk group (n = 272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing.ResultsA total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n = 322) and the RS < 18 low-risk group (3.4%, n = 703), as well as between the AAMC high-risk group (22.8%, n = 230) and the RS > 30 high-risk group (23.0%, n = 141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n = 739) and 24.2% for the high-risk group (n = 272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing.AAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk.ConclusionsAAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk.  | 
    
| Author | Rosman, M. Jackson, R.S. Fujii, T. James, A. Gage, M.M. Le Du, F. Tafra, L. Raghavendra, A. Ueno, N.T. Espinosa Fernandez, J.R. Mylander, W.C. Sinha, A.K.  | 
    
| AuthorAffiliation | 3 Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA 2 The Rebecca Fortney Breast Center, Anne Arundel Medical Center, Annapolis 1 Department of Surgery, Johns Hopkins Hospital, Baltimore  | 
    
| AuthorAffiliation_xml | – name: 1 Department of Surgery, Johns Hopkins Hospital, Baltimore – name: 3 Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA – name: 2 The Rebecca Fortney Breast Center, Anne Arundel Medical Center, Annapolis  | 
    
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| Cites_doi | 10.1016/j.clbc.2015.04.006 10.1038/modpathol.2008.54 10.1200/JCO.2010.31.2835 10.1056/NEJMoa041588 10.1016/j.clbc.2016.06.012 10.1038/modpathol.2017.41 10.1186/bcr2607 10.1038/s41523-017-0033-7 10.1200/JCO.2005.04.7985 10.1016/j.clbc.2015.06.006 10.1007/s10549-017-4170-3 10.1200/JCO.2012.46.1558 10.1016/j.breast.2013.04.008 10.1038/modpathol.2013.36 10.1056/NEJMoa1510764 10.1111/tbj.12126 10.1200/JCO.2015.63.5383 10.1200/JCO.2011.35.3714  | 
    
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| Copyright | 2018 THE AUTHORS The Author(s) 2018. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com. 2018  | 
    
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| Issue | 5 | 
    
| Keywords | early breast cancer recurrence 21-gene assay prognosis pathological assessment  | 
    
| Language | English | 
    
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Prof. Naoto T. Ueno, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe, Unit 1354, Houston, TX 77030, USA. Tel: +1-713-792-8754; Fax: +1-888-375-2139; E-mail: nueno@mdanderson.org  | 
    
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| References | Tang, Cuzick, Costantino (bb0085) 2011; 29 BreastCancer.org. Oncotype DX Test Gage, Rosman, Mylander (bb0035) 2015; 15 Orucevic, Bell, McNabb, Heidel (bb0045) 2017; 163 Farrugia, Landmann, Zhu (bb0095) 2017; 30 Sparano, Gray, Makower (bb0030) 2015; 373 Milburn, Rosman, Mylander, Tafra (bb0070) 2013; 19 Gluz, Nitz, Christgen (bb0050) 2016; 34 Dowsett, Sestak, Lopez-Knowles (bb0105) 2013; 31 Rakha, Reis-Filho, Baehner (bb0040) 2010; 12 Paik, Shak, Tang (bb0010) 2004; 351 (5 March 2018, date last accessed). Le Du, Gonzalez-Angulo, Park (bb0100) 2015; 15 National Comprehensive Cancer Network. Breast Cancer (Version 2.2017). Paik, Tang, Shak (bb0015) 2006; 24 Cuzick, Dowsett, Pineda (bb0065) 2011; 29 Klein, Dabbs, Shuai (bb0080) 2013; 26 (2 March 2018, date last accessed). Stemmer, Steiner, Rizel (bb0055) 2017; 3 Ingoldsby, Webber, Wall (bb0075) 2013; 22 Flanagan, Dabbs, Brufsky (bb0090) 2008; 21 Ono, Tsuda, Yoshida (bb0060) 2017; 17 10.1093/annonc/mdy074_bb0025 Sparano (10.1093/annonc/mdy074_bb0030) 2015; 373 Ono (10.1093/annonc/mdy074_bb0060) 2017; 17 Flanagan (10.1093/annonc/mdy074_bb0090) 2008; 21 Ingoldsby (10.1093/annonc/mdy074_bb0075) 2013; 22 Tang (10.1093/annonc/mdy074_bb0085) 2011; 29 Paik (10.1093/annonc/mdy074_bb0010) 2004; 351 Orucevic (10.1093/annonc/mdy074_bb0045) 2017; 163 Milburn (10.1093/annonc/mdy074_bb0070) 2013; 19 Paik (10.1093/annonc/mdy074_bb0015) 2006; 24 Stemmer (10.1093/annonc/mdy074_bb0055) 2017; 3 Farrugia (10.1093/annonc/mdy074_bb0095) 2017; 30 Le Du (10.1093/annonc/mdy074_bb0100) 2015; 15 Rakha (10.1093/annonc/mdy074_bb0040) 2010; 12 Dowsett (10.1093/annonc/mdy074_bb0105) 2013; 31 10.1093/annonc/mdy074_bb0020 Cuzick (10.1093/annonc/mdy074_bb0065) 2011; 29 Gage (10.1093/annonc/mdy074_bb0035) 2015; 15 Gluz (10.1093/annonc/mdy074_bb0050) 2016; 34 Klein (10.1093/annonc/mdy074_bb0080) 2013; 26 29635411 - Ann Oncol. 2018 May 1;29(5):1096-1098  | 
    
| References_xml | – volume: 351 start-page: 2817 year: 2004 end-page: 2826 ident: bb0010 article-title: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer publication-title: N Engl J Med – volume: 17 start-page: 41 year: 2017 end-page: 47 ident: bb0060 article-title: Prognostic significance of progesterone receptor expression in estrogen-receptor positive, HER2-negative, node-negative invasive breast cancer with a low Ki-67 Labeling Index publication-title: Clin Breast Cancer – volume: 26 start-page: 658 year: 2013 end-page: 664 ident: bb0080 article-title: Prediction of the oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis publication-title: Modern Pathol – reference: (2 March 2018, date last accessed). – volume: 15 start-page: 467 year: 2015 end-page: 472 ident: bb0035 article-title: A validated model for identifying patients unlikely to benefit from the 21-gene recurrence score assay publication-title: Clin Breast Cancer – volume: 163 start-page: 51 year: 2017 end-page: 61 ident: bb0045 article-title: Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data publication-title: Breast Cancer Res Treat – volume: 12 start-page: 207. year: 2010 ident: bb0040 article-title: Breast cancer prognostic classification in the molecular era: the role of histological grade publication-title: Breast Cancer Res – volume: 3 start-page: 32 year: 2017 ident: bb0055 article-title: Clinical outcomes in ER+ HER2-node-positive breast cancer patients who were treated according to the Recurrence Score results: evidence from a large prospectively designed registry publication-title: NPJ Breast Cancer – reference: National Comprehensive Cancer Network. Breast Cancer (Version 2.2017). – volume: 373 start-page: 2005 year: 2015 end-page: 2014 ident: bb0030 article-title: Prospective validation of a 21-gene expression assay in breast cancer publication-title: N Engl J Med – volume: 24 start-page: 3726 year: 2006 end-page: 3734 ident: bb0015 article-title: Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor–positive breast cancer publication-title: J Clin Oncol – reference: (5 March 2018, date last accessed). – volume: 19 start-page: 357 year: 2013 end-page: 364 ident: bb0070 article-title: Is Oncotype DX recurrence score (RS) of prognostic value once HER2-positive and low-ER expression patients are removed? publication-title: Breast J – volume: 22 start-page: 879 year: 2013 end-page: 886 ident: bb0075 article-title: Prediction of Oncotype DX and TAILORx risk categories using histopathological and immunohistochemical markers by classification and regression tree (CART) analysis publication-title: Breast – volume: 34 start-page: 2341 year: 2016 end-page: 2349 ident: bb0050 article-title: West German Study Group Phase III PlanB Trial: first prospective outcome data for the 21-gene recurrence score assay and concordance of prognostic markers by central and local pathology assessment publication-title: J Clin Oncol – volume: 15 start-page: 458 year: 2015 end-page: 466 ident: bb0100 article-title: Effect of 21-gene RT-PCR assay on adjuvant therapy and outcomes in patients with stage I breast cancer publication-title: Clin Breast Cancer – volume: 30 start-page: 1078 year: 2017 end-page: 1085 ident: bb0095 article-title: Magee Equation 3 predicts pathologic response to neoadjuvant systemic chemotherapy in estrogen receptor positive, HER2 negative/equivocal breast tumors publication-title: Mod Pathol – volume: 29 start-page: 4365 year: 2011 end-page: 4372 ident: bb0085 article-title: Risk of recurrence and chemotherapy benefit for patients with node-negative, estrogen receptor–positive breast cancer: recurrence score alone and integrated with pathologic and clinical factors publication-title: J Clin Oncol – volume: 29 start-page: 4273 year: 2011 end-page: 4278 ident: bb0065 article-title: Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer publication-title: J Clin Oncol – volume: 21 start-page: 1255 year: 2008 end-page: 1261 ident: bb0090 article-title: Histopathologic variables predict Oncotype DX recurrence score publication-title: Mod Pathol – reference: BreastCancer.org. Oncotype DX Test, – volume: 31 start-page: 2783 year: 2013 end-page: 2790 ident: bb0105 article-title: Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy publication-title: J Clin Oncol – volume: 15 start-page: 467 issue: 6 year: 2015 ident: 10.1093/annonc/mdy074_bb0035 article-title: A validated model for identifying patients unlikely to benefit from the 21-gene recurrence score assay publication-title: Clin Breast Cancer doi: 10.1016/j.clbc.2015.04.006 – volume: 21 start-page: 1255 issue: 10 year: 2008 ident: 10.1093/annonc/mdy074_bb0090 article-title: Histopathologic variables predict Oncotype DX recurrence score publication-title: Mod Pathol doi: 10.1038/modpathol.2008.54 – volume: 29 start-page: 4273 issue: 32 year: 2011 ident: 10.1093/annonc/mdy074_bb0065 article-title: Prognostic value of a combined estrogen receptor, progesterone receptor, Ki-67, and human epidermal growth factor receptor 2 immunohistochemical score and comparison with the Genomic Health recurrence score in early breast cancer publication-title: J Clin Oncol doi: 10.1200/JCO.2010.31.2835 – volume: 351 start-page: 2817 issue: 27 year: 2004 ident: 10.1093/annonc/mdy074_bb0010 article-title: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer publication-title: N Engl J Med doi: 10.1056/NEJMoa041588 – volume: 17 start-page: 41 issue: 1 year: 2017 ident: 10.1093/annonc/mdy074_bb0060 article-title: Prognostic significance of progesterone receptor expression in estrogen-receptor positive, HER2-negative, node-negative invasive breast cancer with a low Ki-67 Labeling Index publication-title: Clin Breast Cancer doi: 10.1016/j.clbc.2016.06.012 – volume: 30 start-page: 1078 year: 2017 ident: 10.1093/annonc/mdy074_bb0095 article-title: Magee Equation 3 predicts pathologic response to neoadjuvant systemic chemotherapy in estrogen receptor positive, HER2 negative/equivocal breast tumors publication-title: Mod Pathol doi: 10.1038/modpathol.2017.41 – volume: 12 start-page: 207. issue: 4 year: 2010 ident: 10.1093/annonc/mdy074_bb0040 article-title: Breast cancer prognostic classification in the molecular era: the role of histological grade publication-title: Breast Cancer Res doi: 10.1186/bcr2607 – volume: 3 start-page: 32 issue: 1 year: 2017 ident: 10.1093/annonc/mdy074_bb0055 article-title: Clinical outcomes in ER+ HER2-node-positive breast cancer patients who were treated according to the Recurrence Score results: evidence from a large prospectively designed registry publication-title: NPJ Breast Cancer doi: 10.1038/s41523-017-0033-7 – ident: 10.1093/annonc/mdy074_bb0025 – volume: 24 start-page: 3726 issue: 23 year: 2006 ident: 10.1093/annonc/mdy074_bb0015 article-title: Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor–positive breast cancer publication-title: J Clin Oncol doi: 10.1200/JCO.2005.04.7985 – volume: 15 start-page: 458 issue: 6 year: 2015 ident: 10.1093/annonc/mdy074_bb0100 article-title: Effect of 21-gene RT-PCR assay on adjuvant therapy and outcomes in patients with stage I breast cancer publication-title: Clin Breast Cancer doi: 10.1016/j.clbc.2015.06.006 – ident: 10.1093/annonc/mdy074_bb0020 – volume: 163 start-page: 51 issue: 1 year: 2017 ident: 10.1093/annonc/mdy074_bb0045 article-title: Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data publication-title: Breast Cancer Res Treat doi: 10.1007/s10549-017-4170-3 – volume: 31 start-page: 2783 issue: 22 year: 2013 ident: 10.1093/annonc/mdy074_bb0105 article-title: Comparison of PAM50 risk of recurrence score with Oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy publication-title: J Clin Oncol doi: 10.1200/JCO.2012.46.1558 – volume: 22 start-page: 879 issue: 5 year: 2013 ident: 10.1093/annonc/mdy074_bb0075 article-title: Prediction of Oncotype DX and TAILORx risk categories using histopathological and immunohistochemical markers by classification and regression tree (CART) analysis publication-title: Breast doi: 10.1016/j.breast.2013.04.008 – volume: 26 start-page: 658 year: 2013 ident: 10.1093/annonc/mdy074_bb0080 article-title: Prediction of the oncotype DX recurrence score: use of pathology-generated equations derived by linear regression analysis publication-title: Modern Pathol doi: 10.1038/modpathol.2013.36 – volume: 373 start-page: 2005 issue: 21 year: 2015 ident: 10.1093/annonc/mdy074_bb0030 article-title: Prospective validation of a 21-gene expression assay in breast cancer publication-title: N Engl J Med doi: 10.1056/NEJMoa1510764 – volume: 19 start-page: 357 issue: 4 year: 2013 ident: 10.1093/annonc/mdy074_bb0070 article-title: Is Oncotype DX recurrence score (RS) of prognostic value once HER2-positive and low-ER expression patients are removed? publication-title: Breast J doi: 10.1111/tbj.12126 – volume: 34 start-page: 2341 issue: 20 year: 2016 ident: 10.1093/annonc/mdy074_bb0050 article-title: West German Study Group Phase III PlanB Trial: first prospective outcome data for the 21-gene recurrence score assay and concordance of prognostic markers by central and local pathology assessment publication-title: J Clin Oncol doi: 10.1200/JCO.2015.63.5383 – volume: 29 start-page: 4365 issue: 33 year: 2011 ident: 10.1093/annonc/mdy074_bb0085 article-title: Risk of recurrence and chemotherapy benefit for patients with node-negative, estrogen receptor–positive breast cancer: recurrence score alone and integrated with pathologic and clinical factors publication-title: J Clin Oncol doi: 10.1200/JCO.2011.35.3714 – reference: 29635411 - Ann Oncol. 2018 May 1;29(5):1096-1098  | 
    
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| Snippet | The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into... Abstract Background The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative...  | 
    
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| SubjectTerms | 21-gene assay Algorithms Biomarkers, Tumor - genetics Breast - pathology Breast - surgery Breast Neoplasms - epidemiology Breast Neoplasms - genetics Breast Neoplasms - pathology Breast Neoplasms - therapy Chemotherapy, Adjuvant - methods Cost-Benefit Analysis early breast cancer Female Follow-Up Studies Genetic Testing - economics Genetic Testing - methods Humans Incidence Mastectomy Middle Aged Models, Genetic Neoplasm Grading Neoplasm Recurrence, Local - diagnosis Neoplasm Recurrence, Local - epidemiology Neoplasm Recurrence, Local - genetics Neoplasm Recurrence, Local - prevention & control Neoplasm Staging Original articles pathological assessment Predictive Value of Tests Prognosis Prospective Studies recurrence Risk Assessment - economics Risk Assessment - methods Time Factors Treatment Outcome Tumor Burden - genetics  | 
    
| Title | Combined pathologic‐genomic algorithm for early-stage breast cancer improves cost-effective use of the 21-gene recurrence score assay | 
    
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