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A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer
Background: Despite low aggressiveness in tumor biology and high responsiveness to endocrine therapy, subgroups of patients with estrogen receptor-positive/HER2-negative (ER+/HER2-) breast cancer relapse early in the first two years after initiation of endocrine therapy, indicating potential endocri...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518385/ https://www.ncbi.nlm.nih.gov/pubmed/33042787 http://dx.doi.org/10.3389/fonc.2020.01335 |
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author | Lin, Caijin Wu, Jiayi Lin, Lin Fei, Xiaochun Chen, Xiaosong Huang, Ou He, Jianrong Chen, Weiguo Li, Yafen Shen, Kunwei Zhu, Li |
author_facet | Lin, Caijin Wu, Jiayi Lin, Lin Fei, Xiaochun Chen, Xiaosong Huang, Ou He, Jianrong Chen, Weiguo Li, Yafen Shen, Kunwei Zhu, Li |
author_sort | Lin, Caijin |
collection | PubMed |
description | Background: Despite low aggressiveness in tumor biology and high responsiveness to endocrine therapy, subgroups of patients with estrogen receptor-positive/HER2-negative (ER+/HER2-) breast cancer relapse early in the first two years after initiation of endocrine therapy, indicating potential endocrine resistance. Accordingly, we attempted to establish a scoring system to inform the first-2-year prognosis (F2P Score). Methods: Patients with node-negative ER+/HER2- breast cancer and complete data of gene expressions in a 21-gene panel were retrospectively retrieved from Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB). The F2P Score was established based on the clinical and genomic variables associated with the first-2-year relapse after shrinkage correction and validated using the bootstrap resampling method. Model performance was quantified by Harrell's concordance-index (C-index) and Bayesian information criteria (BIC). Results: The F2P Score was established by integrating the clinical (age and tumor size) and genomic (ESR1, PGR, BCL2, CD68, GSTM1, and BAG1) variables with a C-index of 0.71 and BIC of 397.46. Bootstrap C-index was 0.72 (95% CI, 0.62–0.81) and BIC was 396.75 (95% CI, 252.37–541.13). A higher score indicated an increased likelihood of a first-2-year relapse, when used as continuous (HR, 2.94; 95% CI, 1.87–4.61) or categorical (HR, 3.68; 95% CI, 1.70–8.00) predictors in multivariate analysis. Both continuous and categorical F2P Score also remained prognostic for overall survival and other endpoints. No significant interaction was observed between the F2P Score and treatment subgroups. Additionally, the F2P Score outperformed the IHC4, clinical treatment score and 21-gene test in predicting first-2-year relapse. Conclusion: The F2P Score reported herein, integrating the clinicopathological and genomic variables, may inform prognosis and endocrine responsiveness. After the benefits and risks have been considered, treatment escalation may be an alternative strategy for patients with a higher score. |
format | Online Article Text |
id | pubmed-7518385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75183852020-10-09 A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer Lin, Caijin Wu, Jiayi Lin, Lin Fei, Xiaochun Chen, Xiaosong Huang, Ou He, Jianrong Chen, Weiguo Li, Yafen Shen, Kunwei Zhu, Li Front Oncol Oncology Background: Despite low aggressiveness in tumor biology and high responsiveness to endocrine therapy, subgroups of patients with estrogen receptor-positive/HER2-negative (ER+/HER2-) breast cancer relapse early in the first two years after initiation of endocrine therapy, indicating potential endocrine resistance. Accordingly, we attempted to establish a scoring system to inform the first-2-year prognosis (F2P Score). Methods: Patients with node-negative ER+/HER2- breast cancer and complete data of gene expressions in a 21-gene panel were retrospectively retrieved from Shanghai Jiao Tong University Breast Cancer Database (SJTU-BCDB). The F2P Score was established based on the clinical and genomic variables associated with the first-2-year relapse after shrinkage correction and validated using the bootstrap resampling method. Model performance was quantified by Harrell's concordance-index (C-index) and Bayesian information criteria (BIC). Results: The F2P Score was established by integrating the clinical (age and tumor size) and genomic (ESR1, PGR, BCL2, CD68, GSTM1, and BAG1) variables with a C-index of 0.71 and BIC of 397.46. Bootstrap C-index was 0.72 (95% CI, 0.62–0.81) and BIC was 396.75 (95% CI, 252.37–541.13). A higher score indicated an increased likelihood of a first-2-year relapse, when used as continuous (HR, 2.94; 95% CI, 1.87–4.61) or categorical (HR, 3.68; 95% CI, 1.70–8.00) predictors in multivariate analysis. Both continuous and categorical F2P Score also remained prognostic for overall survival and other endpoints. No significant interaction was observed between the F2P Score and treatment subgroups. Additionally, the F2P Score outperformed the IHC4, clinical treatment score and 21-gene test in predicting first-2-year relapse. Conclusion: The F2P Score reported herein, integrating the clinicopathological and genomic variables, may inform prognosis and endocrine responsiveness. After the benefits and risks have been considered, treatment escalation may be an alternative strategy for patients with a higher score. Frontiers Media S.A. 2020-09-11 /pmc/articles/PMC7518385/ /pubmed/33042787 http://dx.doi.org/10.3389/fonc.2020.01335 Text en Copyright © 2020 Lin, Wu, Lin, Fei, Chen, Huang, He, Chen, Li, Shen and Zhu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Lin, Caijin Wu, Jiayi Lin, Lin Fei, Xiaochun Chen, Xiaosong Huang, Ou He, Jianrong Chen, Weiguo Li, Yafen Shen, Kunwei Zhu, Li A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title | A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title_full | A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title_fullStr | A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title_full_unstemmed | A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title_short | A Novel Prognostic Scoring System Integrating Gene Expressions and Clinicopathological Characteristics to Predict Very Early Relapse in Node-Negative Estrogen Receptor-Positive/HER2-Negative Breast Cancer |
title_sort | novel prognostic scoring system integrating gene expressions and clinicopathological characteristics to predict very early relapse in node-negative estrogen receptor-positive/her2-negative breast cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518385/ https://www.ncbi.nlm.nih.gov/pubmed/33042787 http://dx.doi.org/10.3389/fonc.2020.01335 |
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