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A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database
Whether patients with medullary breast carcinoma (MBC) receive chemotherapy is controversial. Therefore, the aim of our study was to screen out patients with MBC who benefit from chemotherapy. We enrolled 618 consecutive patients with MBC from The Surveillance, Epidemiology, and End Results (SEER) d...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317966/ https://www.ncbi.nlm.nih.gov/pubmed/37400489 http://dx.doi.org/10.1038/s41598-023-37915-2 |
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author | Chen, Heyan Pu, Shengyu Wang, Lizhao Zhang, Huimin Yan, Yu He, Jianjun Zhang, Jian |
author_facet | Chen, Heyan Pu, Shengyu Wang, Lizhao Zhang, Huimin Yan, Yu He, Jianjun Zhang, Jian |
author_sort | Chen, Heyan |
collection | PubMed |
description | Whether patients with medullary breast carcinoma (MBC) receive chemotherapy is controversial. Therefore, the aim of our study was to screen out patients with MBC who benefit from chemotherapy. We enrolled 618 consecutive patients with MBC from The Surveillance, Epidemiology, and End Results (SEER) database (2010–2018). Cox regression analysis was used to identify independent prognostic factors. Next, a nomogram was constructed and evaluated using calibration plots and the area under the curve (AUC) of receiver operating characteristic (ROC) curves. Kaplan‒Meier curves were used to evaluate the overall survival (OS) benefit of chemotherapy in different risk groups. A total of 618 MBC patients were involved in our study, and an 8:2 ratio was used to randomly split them into a training cohort (n = 545) and a validation cohort (n = 136). Next, a nomogram predicting 3- and 5-year OS rates was constructed based on the five independent factors (age at diagnosis, T stage, N status, subtype and radiation). The nomogram AUCs for 3- and 5-year OS (training set: 0.793 and 0.797; validation set: 0.781 and 0.823) and calibration plots exhibited good discriminative and predictive ability. Additionally, a novel risk classification system for MBC patients demonstrated that we do not have enough evidence to support the benefit effect of chemotherapy for the high-risk group as the result is not statistically significant (total population: p = 0.180; training set: p = 0.340) but could improve OS in the low-risk group (total population: p = 0.001; training set: p = 0.001). Our results suggested that chemotherapy should be selected more carefully for high-risk groups based on a combination of factors and that the possibility of exemption from chemotherapy should be confirmed by more clinical trials in the future. |
format | Online Article Text |
id | pubmed-10317966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103179662023-07-05 A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database Chen, Heyan Pu, Shengyu Wang, Lizhao Zhang, Huimin Yan, Yu He, Jianjun Zhang, Jian Sci Rep Article Whether patients with medullary breast carcinoma (MBC) receive chemotherapy is controversial. Therefore, the aim of our study was to screen out patients with MBC who benefit from chemotherapy. We enrolled 618 consecutive patients with MBC from The Surveillance, Epidemiology, and End Results (SEER) database (2010–2018). Cox regression analysis was used to identify independent prognostic factors. Next, a nomogram was constructed and evaluated using calibration plots and the area under the curve (AUC) of receiver operating characteristic (ROC) curves. Kaplan‒Meier curves were used to evaluate the overall survival (OS) benefit of chemotherapy in different risk groups. A total of 618 MBC patients were involved in our study, and an 8:2 ratio was used to randomly split them into a training cohort (n = 545) and a validation cohort (n = 136). Next, a nomogram predicting 3- and 5-year OS rates was constructed based on the five independent factors (age at diagnosis, T stage, N status, subtype and radiation). The nomogram AUCs for 3- and 5-year OS (training set: 0.793 and 0.797; validation set: 0.781 and 0.823) and calibration plots exhibited good discriminative and predictive ability. Additionally, a novel risk classification system for MBC patients demonstrated that we do not have enough evidence to support the benefit effect of chemotherapy for the high-risk group as the result is not statistically significant (total population: p = 0.180; training set: p = 0.340) but could improve OS in the low-risk group (total population: p = 0.001; training set: p = 0.001). Our results suggested that chemotherapy should be selected more carefully for high-risk groups based on a combination of factors and that the possibility of exemption from chemotherapy should be confirmed by more clinical trials in the future. Nature Publishing Group UK 2023-07-03 /pmc/articles/PMC10317966/ /pubmed/37400489 http://dx.doi.org/10.1038/s41598-023-37915-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/ Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chen, Heyan Pu, Shengyu Wang, Lizhao Zhang, Huimin Yan, Yu He, Jianjun Zhang, Jian A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title | A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title_full | A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title_fullStr | A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title_full_unstemmed | A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title_short | A risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based SEER database |
title_sort | risk stratification model to predict chemotherapy benefit in medullary carcinoma of the breast: a population-based seer database |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317966/ https://www.ncbi.nlm.nih.gov/pubmed/37400489 http://dx.doi.org/10.1038/s41598-023-37915-2 |
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