Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population: Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy

Ko Un Park, Yalei Chen, Dhananjay Chitale, Sarah Choi, Haythem Ali, S. David Nathanson, Jessica Bensenhaver, Erica Proctor, Lindsay Petersen, Randa Loutfi, Alyson Simonds, Marcia Kuklinski, Thomas Doyle, Vrushali Dabak, Kim Cole, Melissa Davis, Lisa Newman

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Introduction: The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging. Methods: Primary surgery patients with Oncotype DX RS testing 2012–2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm. Results: Of 394 primary surgery patients—60.4% white American; 31.0% African American—RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100%); conversely, of 16 cases generating high-risk RS, only 2 did not respond. Conclusions: Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.

Original languageEnglish (US)
Pages (from-to)1921-1927
Number of pages7
JournalAnnals of surgical oncology
Volume25
Issue number7
DOIs
StatePublished - Jul 1 2018

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Breast Neoplasms
Recurrence
Drug Therapy
Population
Genes
Hormones
Neoplasms
Statistical Models
Adjuvant Chemotherapy
Transcriptome
African Americans
Area Under Curve
Histology
Databases

ASJC Scopus subject areas

  • Surgery
  • Oncology

Cite this

Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population : Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy. / Park, Ko Un; Chen, Yalei; Chitale, Dhananjay; Choi, Sarah; Ali, Haythem; Nathanson, S. David; Bensenhaver, Jessica; Proctor, Erica; Petersen, Lindsay; Loutfi, Randa; Simonds, Alyson; Kuklinski, Marcia; Doyle, Thomas; Dabak, Vrushali; Cole, Kim; Davis, Melissa; Newman, Lisa.

In: Annals of surgical oncology, Vol. 25, No. 7, 01.07.2018, p. 1921-1927.

Research output: Contribution to journalArticle

Park, KU, Chen, Y, Chitale, D, Choi, S, Ali, H, Nathanson, SD, Bensenhaver, J, Proctor, E, Petersen, L, Loutfi, R, Simonds, A, Kuklinski, M, Doyle, T, Dabak, V, Cole, K, Davis, M & Newman, L 2018, 'Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population: Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy', Annals of surgical oncology, vol. 25, no. 7, pp. 1921-1927. https://doi.org/10.1245/s10434-018-6440-7
Park, Ko Un ; Chen, Yalei ; Chitale, Dhananjay ; Choi, Sarah ; Ali, Haythem ; Nathanson, S. David ; Bensenhaver, Jessica ; Proctor, Erica ; Petersen, Lindsay ; Loutfi, Randa ; Simonds, Alyson ; Kuklinski, Marcia ; Doyle, Thomas ; Dabak, Vrushali ; Cole, Kim ; Davis, Melissa ; Newman, Lisa. / Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population : Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy. In: Annals of surgical oncology. 2018 ; Vol. 25, No. 7. pp. 1921-1927.
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abstract = "Introduction: The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging. Methods: Primary surgery patients with Oncotype DX RS testing 2012–2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm. Results: Of 394 primary surgery patients—60.4{\%} white American; 31.0{\%} African American—RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100{\%}); conversely, of 16 cases generating high-risk RS, only 2 did not respond. Conclusions: Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.",
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T1 - Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population

T2 - Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy

AU - Park, Ko Un

AU - Chen, Yalei

AU - Chitale, Dhananjay

AU - Choi, Sarah

AU - Ali, Haythem

AU - Nathanson, S. David

AU - Bensenhaver, Jessica

AU - Proctor, Erica

AU - Petersen, Lindsay

AU - Loutfi, Randa

AU - Simonds, Alyson

AU - Kuklinski, Marcia

AU - Doyle, Thomas

AU - Dabak, Vrushali

AU - Cole, Kim

AU - Davis, Melissa

AU - Newman, Lisa

PY - 2018/7/1

Y1 - 2018/7/1

N2 - Introduction: The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging. Methods: Primary surgery patients with Oncotype DX RS testing 2012–2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm. Results: Of 394 primary surgery patients—60.4% white American; 31.0% African American—RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100%); conversely, of 16 cases generating high-risk RS, only 2 did not respond. Conclusions: Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.

AB - Introduction: The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging. Methods: Primary surgery patients with Oncotype DX RS testing 2012–2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm. Results: Of 394 primary surgery patients—60.4% white American; 31.0% African American—RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100%); conversely, of 16 cases generating high-risk RS, only 2 did not respond. Conclusions: Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.

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