Cargando…
Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer
BACKGROUND: Triple-negative breast cancer (TNBC) patients who recur at different times are associated with distinct biological characteristics and prognoses. Research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe the characteristics of recurrence, predictors for rela...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978400/ https://www.ncbi.nlm.nih.gov/pubmed/36874102 http://dx.doi.org/10.3389/fonc.2023.1119611 |
_version_ | 1784899516613263360 |
---|---|
author | Cai, Shuang-Long Liu, Jing-Jing Liu, Ying-Xue Yu, Shao-Hong Liu, Xu Lin, Xiu-Quan Chen, Hong-Dan Fang, Xuan Ma, Tao Li, Ya-Qing Li, Ying Li, Chun-Yan Zhang, Sheng Chen, Xiao-Geng Guo, Xiao-Jing Zhang, Jin |
author_facet | Cai, Shuang-Long Liu, Jing-Jing Liu, Ying-Xue Yu, Shao-Hong Liu, Xu Lin, Xiu-Quan Chen, Hong-Dan Fang, Xuan Ma, Tao Li, Ya-Qing Li, Ying Li, Chun-Yan Zhang, Sheng Chen, Xiao-Geng Guo, Xiao-Jing Zhang, Jin |
author_sort | Cai, Shuang-Long |
collection | PubMed |
description | BACKGROUND: Triple-negative breast cancer (TNBC) patients who recur at different times are associated with distinct biological characteristics and prognoses. Research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe the characteristics of recurrence, predictors for relapse, and prognosis in rrTNBC patients. METHODS: Clinicopathological data of 1584 TNBC patients from 2014 to 2016 were retrospectively reviewed. The characteristics of recurrence were compared between patients with RR-TNBC and slow relapse TNBC(SR-TNBC). All TNBC patients were randomly divided into a training set and a validation set to find predictors for rapid relapse. The multivariate logistic regression model was used to analyze the data of the training set. C-index and brier score analysis for predicting rapid relapse in the validation set was used to evaluate the discrimination and accuracy of the multivariate logistic model. Prognostic measurements were analyzed in all TNBC patients. RESULTS: Compared with SR-TNBC patients, RR-TNBC patients tended to have a higher T staging, N staging, TNM staging, and low expression of stromal tumor-infiltrating lymphocytes (sTILs). The recurring characteristics were prone to appear as distant metastasis at the first relapse. The first metastatic site was apt to visceral metastasis and less likely to have chest wall or regional lymph node metastasis. Six predictors (postmenopausal status, metaplastic breast cancer,≥pT3 staging,≥pN1 staging, sTIL intermediate/high expression, and Her2 [1+]) were used to construct the predictive model of rapid relapse in TNBC patients. The C-index and brier score in the validation set was 0.861 and 0.095, respectively. This suggested that the predictive model had high discrimination and accuracy. The prognostic data for all TNBC patients showed that RR-TNBC patients had the worst prognosis, followed by SR-TNBC patients. CONCLUSION: RR-TNBC patients were associated with unique biological characteristics and worse outcomes compared to non-RR-TNBC patients. |
format | Online Article Text |
id | pubmed-9978400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99784002023-03-03 Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer Cai, Shuang-Long Liu, Jing-Jing Liu, Ying-Xue Yu, Shao-Hong Liu, Xu Lin, Xiu-Quan Chen, Hong-Dan Fang, Xuan Ma, Tao Li, Ya-Qing Li, Ying Li, Chun-Yan Zhang, Sheng Chen, Xiao-Geng Guo, Xiao-Jing Zhang, Jin Front Oncol Oncology BACKGROUND: Triple-negative breast cancer (TNBC) patients who recur at different times are associated with distinct biological characteristics and prognoses. Research on rapid-relapse TNBC (RR-TNBC) is sparse. In this study, we aimed to describe the characteristics of recurrence, predictors for relapse, and prognosis in rrTNBC patients. METHODS: Clinicopathological data of 1584 TNBC patients from 2014 to 2016 were retrospectively reviewed. The characteristics of recurrence were compared between patients with RR-TNBC and slow relapse TNBC(SR-TNBC). All TNBC patients were randomly divided into a training set and a validation set to find predictors for rapid relapse. The multivariate logistic regression model was used to analyze the data of the training set. C-index and brier score analysis for predicting rapid relapse in the validation set was used to evaluate the discrimination and accuracy of the multivariate logistic model. Prognostic measurements were analyzed in all TNBC patients. RESULTS: Compared with SR-TNBC patients, RR-TNBC patients tended to have a higher T staging, N staging, TNM staging, and low expression of stromal tumor-infiltrating lymphocytes (sTILs). The recurring characteristics were prone to appear as distant metastasis at the first relapse. The first metastatic site was apt to visceral metastasis and less likely to have chest wall or regional lymph node metastasis. Six predictors (postmenopausal status, metaplastic breast cancer,≥pT3 staging,≥pN1 staging, sTIL intermediate/high expression, and Her2 [1+]) were used to construct the predictive model of rapid relapse in TNBC patients. The C-index and brier score in the validation set was 0.861 and 0.095, respectively. This suggested that the predictive model had high discrimination and accuracy. The prognostic data for all TNBC patients showed that RR-TNBC patients had the worst prognosis, followed by SR-TNBC patients. CONCLUSION: RR-TNBC patients were associated with unique biological characteristics and worse outcomes compared to non-RR-TNBC patients. Frontiers Media S.A. 2023-02-16 /pmc/articles/PMC9978400/ /pubmed/36874102 http://dx.doi.org/10.3389/fonc.2023.1119611 Text en Copyright © 2023 Cai, Liu, Liu, Yu, Liu, Lin, Chen, Fang, Ma, Li, Li, Li, Zhang, Chen, Guo and Zhang https://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 Cai, Shuang-Long Liu, Jing-Jing Liu, Ying-Xue Yu, Shao-Hong Liu, Xu Lin, Xiu-Quan Chen, Hong-Dan Fang, Xuan Ma, Tao Li, Ya-Qing Li, Ying Li, Chun-Yan Zhang, Sheng Chen, Xiao-Geng Guo, Xiao-Jing Zhang, Jin Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title | Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title_full | Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title_fullStr | Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title_full_unstemmed | Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title_short | Characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
title_sort | characteristics of recurrence, predictors for relapse and prognosis of rapid relapse triple-negative breast cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9978400/ https://www.ncbi.nlm.nih.gov/pubmed/36874102 http://dx.doi.org/10.3389/fonc.2023.1119611 |
work_keys_str_mv | AT caishuanglong characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT liujingjing characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT liuyingxue characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT yushaohong characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT liuxu characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT linxiuquan characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT chenhongdan characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT fangxuan characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT matao characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT liyaqing characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT liying characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT lichunyan characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT zhangsheng characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT chenxiaogeng characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT guoxiaojing characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer AT zhangjin characteristicsofrecurrencepredictorsforrelapseandprognosisofrapidrelapsetriplenegativebreastcancer |