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Published in: BMC Cancer 1/2019

Open Access 01-12-2019 | Breast Cancer | Research article

Development and validation of nomograms predicting survival in Chinese patients with triple negative breast cancer

Authors: Yaping Yang, Ying Wang, Heran Deng, Cui Tan, Qian Li, Zhanghai He, Wei Wei, Enxiang Zhou, Qiang Liu, Jieqiong Liu

Published in: BMC Cancer | Issue 1/2019

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Abstract

Background

Triple negative breast cancer (TNBC) is an aggressive and heterogeneous disease. Nomograms predicting outcomes of TNBC are needed for risk management.

Methods

Nomograms were based on an analysis of 296 non-metastatic TNBC patients treated at Sun Yat-sen Memorial Hospital from 2002 to 2014. The end points were disease-free survival (DFS) and overall survival (OS). Predictive accuracy and discriminative ability were evaluated by concordance index (C-index), area under the curve (AUC) and calibration curve, and compared with the American Joint Committee on Cancer (AJCC) staging system, PREDICT and CancerMath. Models were subjected to bootstrap internal validation and external validation using independent cohorts of 191 patients from the second Xiangya Hospital and Peking University Shenzhen Hospital between 2007 and 2012.

Results

On multivariable analysis of training cohort, independent prognostic factors were stromal tumor-infiltrating lymphocytes (TILs), tumor size, node status, and Ki67 index, which were then selected into the nomograms. The calibration curves for probability of DFS and OS showed optimal agreement between nomogram prediction and actual observation. The C-index of nomograms was significantly higher than that of the seventh and eighth AJCC staging system for predicting DFS (training: 0.743 vs 0.666 (P = 0.003) and 0.664 (P = 0.024); validation: 0.784 vs 0.632 (P = 0.02) and 0.607 (P = 0.002)) and OS (training: 0.791 vs 0.683 (P = 0.004) and 0.677 (P < 0.001); validation: 0.783 vs 0.656 (P = 0.006) and 0.606 (P = 0.001)). Our nomograms had larger AUCs compared with PREDICT and CancerMath. In addition, the nomograms showed good performance in stratifying different risk groups of patients both in the training and validation cohorts.

Conclusion

We have developed novel and practical nomograms that can provide individual prediction of DFS and OS for TNBC based on stromal TILs, tumor size, node status, and Ki67 index. Our nomograms may help clinicians in risk consulting and selection of long term survivors.
Appendix
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Metadata
Title
Development and validation of nomograms predicting survival in Chinese patients with triple negative breast cancer
Authors
Yaping Yang
Ying Wang
Heran Deng
Cui Tan
Qian Li
Zhanghai He
Wei Wei
Enxiang Zhou
Qiang Liu
Jieqiong Liu
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2019
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-019-5703-4

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