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A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer
BACKGROUND: Patients with metastatic triple‐negative breast cancer (mTNBC) frequently experience brain metastasis. This study aimed to identify prognostic factors and construct a nomogram for predicting brain metastasis possibility and brain screening benefit in mTNBC patients. METHODS: Patients wit...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666757/ https://www.ncbi.nlm.nih.gov/pubmed/32945619 http://dx.doi.org/10.1002/cam4.3449 |
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author | Lin, Mingxi Jin, Yizi Jin, Jia Wang, Biyun Hu, Xichun Zhang, Jian |
author_facet | Lin, Mingxi Jin, Yizi Jin, Jia Wang, Biyun Hu, Xichun Zhang, Jian |
author_sort | Lin, Mingxi |
collection | PubMed |
description | BACKGROUND: Patients with metastatic triple‐negative breast cancer (mTNBC) frequently experience brain metastasis. This study aimed to identify prognostic factors and construct a nomogram for predicting brain metastasis possibility and brain screening benefit in mTNBC patients. METHODS: Patients with mTNBC treated at our institution between January 2011 and December 2018 were retrospectively analyzed. Fine and Gray's competing risks model was used to identify independent prognostic factors. By integrating these prognostic factors, a competing risk nomogram and risk stratification model were developed and evaluated with concordance index (C‐index) and calibration curves. RESULTS: A total of 472 patients were retrospectively analyzed, including 305 patients in the training set, 78 patients in the validation set I and 89 patients in the validation set II. Four clinicopathological factors were identified as independent prognostic factors in the nomogram: lung metastasis, number of metastatic organ sites, hilar/mediastinal lymph node metastasis and KI‐67 index. The C‐indexes and calibration plots showed that the nomogram exhibited a sufficient level of discrimination. A risk stratification was further generated to divide all the patients into three prognostic groups. The cumulative incidence of brain metastasis at 18 months was 5.3% (95% confidence interval [CI], 2.5%‐9.7%) for patients in the low‐risk group, while 14.3% (95% CI, 9.3%‐20.4%) for patients with intermediate risk and 34.3% (95% CI, 26.8%‐41.9%) for patients with high risk. Routine brain MRI screening improved overall survival in high‐risk group (HR 0.67, 95% CI 0.46‐0.98, P = .039), but not in low‐risk group (HR 0.93, 95% CI 0.57‐1.49, P = .751) and intermediate‐risk group (HR 0.83, 95% CI 0.55‐1.27, P = .386). CONCLUSIONS: We have developed a robust tool that is able to predict subsequent brain metastasis in mTNBC patients. Our model will allow selection of patients at high risk for brain metastasis who might benefit from routine bran MRI screening. |
format | Online Article Text |
id | pubmed-7666757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-76667572020-11-20 A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer Lin, Mingxi Jin, Yizi Jin, Jia Wang, Biyun Hu, Xichun Zhang, Jian Cancer Med Clinical Cancer Research BACKGROUND: Patients with metastatic triple‐negative breast cancer (mTNBC) frequently experience brain metastasis. This study aimed to identify prognostic factors and construct a nomogram for predicting brain metastasis possibility and brain screening benefit in mTNBC patients. METHODS: Patients with mTNBC treated at our institution between January 2011 and December 2018 were retrospectively analyzed. Fine and Gray's competing risks model was used to identify independent prognostic factors. By integrating these prognostic factors, a competing risk nomogram and risk stratification model were developed and evaluated with concordance index (C‐index) and calibration curves. RESULTS: A total of 472 patients were retrospectively analyzed, including 305 patients in the training set, 78 patients in the validation set I and 89 patients in the validation set II. Four clinicopathological factors were identified as independent prognostic factors in the nomogram: lung metastasis, number of metastatic organ sites, hilar/mediastinal lymph node metastasis and KI‐67 index. The C‐indexes and calibration plots showed that the nomogram exhibited a sufficient level of discrimination. A risk stratification was further generated to divide all the patients into three prognostic groups. The cumulative incidence of brain metastasis at 18 months was 5.3% (95% confidence interval [CI], 2.5%‐9.7%) for patients in the low‐risk group, while 14.3% (95% CI, 9.3%‐20.4%) for patients with intermediate risk and 34.3% (95% CI, 26.8%‐41.9%) for patients with high risk. Routine brain MRI screening improved overall survival in high‐risk group (HR 0.67, 95% CI 0.46‐0.98, P = .039), but not in low‐risk group (HR 0.93, 95% CI 0.57‐1.49, P = .751) and intermediate‐risk group (HR 0.83, 95% CI 0.55‐1.27, P = .386). CONCLUSIONS: We have developed a robust tool that is able to predict subsequent brain metastasis in mTNBC patients. Our model will allow selection of patients at high risk for brain metastasis who might benefit from routine bran MRI screening. John Wiley and Sons Inc. 2020-09-18 /pmc/articles/PMC7666757/ /pubmed/32945619 http://dx.doi.org/10.1002/cam4.3449 Text en © 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Clinical Cancer Research Lin, Mingxi Jin, Yizi Jin, Jia Wang, Biyun Hu, Xichun Zhang, Jian A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title | A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title_full | A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title_fullStr | A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title_full_unstemmed | A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title_short | A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
title_sort | risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple‐negative breast cancer |
topic | Clinical Cancer Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666757/ https://www.ncbi.nlm.nih.gov/pubmed/32945619 http://dx.doi.org/10.1002/cam4.3449 |
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