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A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age

BACKGROUND: The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients > 50 years with RS > 25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS...

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Autores principales: Yu, Jing, Wu, Jiayi, Huang, Ou, He, Jianrong, Zhu, Li, Chen, Weiguo, Li, Yafen, Chen, Xiaosong, Shen, Kunwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885620/
https://www.ncbi.nlm.nih.gov/pubmed/33593381
http://dx.doi.org/10.1186/s12967-021-02743-3
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author Yu, Jing
Wu, Jiayi
Huang, Ou
He, Jianrong
Zhu, Li
Chen, Weiguo
Li, Yafen
Chen, Xiaosong
Shen, Kunwei
author_facet Yu, Jing
Wu, Jiayi
Huang, Ou
He, Jianrong
Zhu, Li
Chen, Weiguo
Li, Yafen
Chen, Xiaosong
Shen, Kunwei
author_sort Yu, Jing
collection PubMed
description BACKGROUND: The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients > 50 years with RS > 25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS. METHODS: We included patients diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative who underwent the 21-gene RS testing and aged > 50 years. The primary outcome was high-risk RS (> 25). Univariate and multivariate analyses were performed to identify significant predictors. A predictive nomogram based on logistic model was developed and evaluated with receiver operating characteristic (ROC) curves. The nomogram was internally validated for discrimination and calibration with bootstrapping method, and externally validated in another cohort. We then assessed the nomogram in different subgroups of patients and compared it with several published models. RESULTS: A total of 1100 patients were included. Five clinicopathological parameters were used as predictors of a high-risk RS, including tumor grade, histologic subtype, ER expression, PR expression, and Ki-67 index. The area under the curve (AUC) was 0.798 (95% CI 0.772–0.825) and optimism adjusted AUC was 0.794 (95% CI 0.781–0.822). External validation demonstrated an AUC value of 0.746 (95% CI 0.685–0.807), which had no significant difference with the training cohort (P = 0.124). Calibration plots indicated that the nomogram-predicted results were well fitted to the actual outcomes in both internal and external validation. The nomogram had better discriminate ability in patients who had tumors > 2 cm (AUC = 0.847, 95% CI 0.804–0.890). When compared with four other existing models, similar AUC was observed between our nomogram and the model constructed by discriminate Lee et al. CONCLUSIONS: We developed a user-friendly nomogram to predict the high-risk RS in luminal breast cancer patients who were older than 50 years of age, which could guide treatment decision making for those who have no access to the 21-gene RS testing.
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spelling pubmed-78856202021-02-22 A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age Yu, Jing Wu, Jiayi Huang, Ou He, Jianrong Zhu, Li Chen, Weiguo Li, Yafen Chen, Xiaosong Shen, Kunwei J Transl Med Research BACKGROUND: The 21-gene recurrence score (RS) testing can predict the prognosis for luminal breast cancer patients. Meanwhile, patients > 50 years with RS > 25 have improved survival with adjuvant chemotherapy. The current study aimed to develop a nomogram with routine parameters to predict RS. METHODS: We included patients diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative who underwent the 21-gene RS testing and aged > 50 years. The primary outcome was high-risk RS (> 25). Univariate and multivariate analyses were performed to identify significant predictors. A predictive nomogram based on logistic model was developed and evaluated with receiver operating characteristic (ROC) curves. The nomogram was internally validated for discrimination and calibration with bootstrapping method, and externally validated in another cohort. We then assessed the nomogram in different subgroups of patients and compared it with several published models. RESULTS: A total of 1100 patients were included. Five clinicopathological parameters were used as predictors of a high-risk RS, including tumor grade, histologic subtype, ER expression, PR expression, and Ki-67 index. The area under the curve (AUC) was 0.798 (95% CI 0.772–0.825) and optimism adjusted AUC was 0.794 (95% CI 0.781–0.822). External validation demonstrated an AUC value of 0.746 (95% CI 0.685–0.807), which had no significant difference with the training cohort (P = 0.124). Calibration plots indicated that the nomogram-predicted results were well fitted to the actual outcomes in both internal and external validation. The nomogram had better discriminate ability in patients who had tumors > 2 cm (AUC = 0.847, 95% CI 0.804–0.890). When compared with four other existing models, similar AUC was observed between our nomogram and the model constructed by discriminate Lee et al. CONCLUSIONS: We developed a user-friendly nomogram to predict the high-risk RS in luminal breast cancer patients who were older than 50 years of age, which could guide treatment decision making for those who have no access to the 21-gene RS testing. BioMed Central 2021-02-16 /pmc/articles/PMC7885620/ /pubmed/33593381 http://dx.doi.org/10.1186/s12967-021-02743-3 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Yu, Jing
Wu, Jiayi
Huang, Ou
He, Jianrong
Zhu, Li
Chen, Weiguo
Li, Yafen
Chen, Xiaosong
Shen, Kunwei
A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title_full A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title_fullStr A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title_full_unstemmed A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title_short A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age
title_sort nomogram to predict the high-risk rs in hr+/her2-breast cancer patients older than 50 years of age
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885620/
https://www.ncbi.nlm.nih.gov/pubmed/33593381
http://dx.doi.org/10.1186/s12967-021-02743-3
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