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 inAnnals of oncology Vol. 29; no. 5; pp. 1280 - 1285
Main Authors Gage, M.M., Mylander, W.C., Rosman, M., Fujii, T., Le Du, F., Raghavendra, A., Sinha, A.K., Espinosa Fernandez, J.R., James, A., Ueno, N.T., Tafra, L., Jackson, R.S.
Format Journal Article
LanguageEnglish
Published England Elsevier Ltd 01.05.2018
Oxford University Press
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Online AccessGet full text
ISSN0923-7534
1569-8041
1569-8041
DOI10.1093/annonc/mdy074

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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.
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
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– name: 3 Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
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Issue 5
Keywords early breast cancer
recurrence
21-gene assay
prognosis
pathological assessment
Language English
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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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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
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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
URI https://dx.doi.org/10.1093/annonc/mdy074
https://www.ncbi.nlm.nih.gov/pubmed/29788166
https://www.proquest.com/docview/2043183209
https://pubmed.ncbi.nlm.nih.gov/PMC5961181
http://www.annalsofoncology.org/article/S0923753419345430/pdf
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