Literature DB >> 32931976

Primary tumor removal improves the prognosis in patients with stage IV breast cancer: A population-based study (cohort study).

Nan Yao1, Wenqiang Li1, Tong Liu1, Sarah Tan Siyin2, Xiufeng Chen1, Weiqi Wang1, Ning Duan1, Yi-Tsun Chen3, Jun Qu4.   

Abstract

Adjuvant therapy including chemotherapy, hormonal therapy, and radiotherapy were often used as a common stereotypy for female stage IV breast cancer rather than surgery. This study aimed to define the role of local surgery in metastatic breast cancer. Female metastatic breast cancer patients were identified in the Surveillance, Epidemiology, and End Results (SEER) program data (2010-2013). We compared survival time between patients who received primary tumor removal (PTR) versus those who did not. Multivariate Cox regression models and competitive risk models were built to adjust potential confounders. Of 7669 female stage IV breast cancer patients, 2704 (35.3%) had surgery on their breast tumor and 4965 (64.7%) did not. In the entire cohort, women who underwent PTR had a 45% reduced risk of breast cancer-related death (multi-adjusted hazard ratio [HR], 0.55; 95% CI, 0.50 to 0.60) compared with women who did not undergo PTR (P < 0.001). In a cause-specific hazard model (CS model), the multivariable HRs (95% CI) for the association of PTR with breast cancer related-death were 0.54 (0.50-0.60) in the multivariate-adjusted analysis. Similar results were also observed in the sub-distribution hazard function model (SD model) with corresponding multivariate HRs (95%CI) of 0.57 (0.52-0.63). Our study suggested that PTR was associated with improved survival in female stage IV breast cancer patients. The role of PTR in these patients needs to be re-evaluated.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Competing risk models; Primary tumor removal; Prognosis; Prospective; Stage IV breast Cancer

Mesh:

Year:  2020        PMID: 32931976     DOI: 10.1016/j.ijsu.2020.08.056

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   13.400


  2 in total

1.  An app to classify a 5-year survival in patients with breast cancer using the convolutional neural networks (CNN) in Microsoft Excel: Development and usability study.

Authors:  Cheng-Yao Lin; Tsair-Wei Chien; Yen-Hsun Chen; Yen-Ling Lee; Shih-Bin Su
Journal:  Medicine (Baltimore)       Date:  2022-01-28       Impact factor: 1.889

2.  Development and validation of nomograms for predicting survival in patients with de novo metastatic triple-negative breast cancer.

Authors:  Mao-Shan Chen; Peng-Cheng Liu; Jin-Zhi Yi; Li Xu; Tao He; Hao Wu; Ji-Qiao Yang; Qing Lv
Journal:  Sci Rep       Date:  2022-08-29       Impact factor: 4.996

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.