Xiang Cui1, Deba Song1, Xiaoxu Li1. 1. Department of Thyroid and Breast Surgery, The First People's Hospital of Shangqiu, Shangqiu, China.
Abstract
BACKGROUND: Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with poorest clinical outcomes. Patients of childbearing age have a higher probability of TNBC diagnosis, with more demands on maintenance and restoration of physical and psychosocial function. This study aimed to design effective and comprehensive nomograms to predict survival in these patients. METHODS: We used the SEER database to identify patients with TNBC aged between 18 and 45 and randomly classified these patients into a training (n=2,296) and a validation (n=2,297) cohort. Nomograms for estimating overall survival (OS) and breast cancer-specific survival (BCSS) were generated based on multivariate Cox proportional hazards models and competing-risk models in the training cohort. The performances of the nomograms were quantified in the validation cohort using calibration curves, time-dependent receiver operating characteristic (ROC) curves and Harrell's concordance index (C-index). RESULTS: A total of 4,593 TNBC patients of childbearing age were enrolled. Four prognostic factors for OS and six for BCSS were identified and incorporated to construct nomograms. In the validation cohort, calibration curves showed excellent agreement between nomogram-predicted and actual survival data. The nomograms also achieved relatively high Harrell's C-indexes and areas under the time-dependent ROC curves for estimating OS and BCSS in both training and validation cohorts. CONCLUSIONS: Independent prognostic factors were identified, and used to develop nomograms to predict OS and BCSS in childbearing-age patients with TNBC. These models could enable individualized risk estimation and risk-adapted treatment for these patients.
BACKGROUND: Triple-negative breast cancer (TNBC) is one of the most aggressive subtypes of breast cancer with poorest clinical outcomes. Patients of childbearing age have a higher probability of TNBC diagnosis, with more demands on maintenance and restoration of physical and psychosocial function. This study aimed to design effective and comprehensive nomograms to predict survival in these patients. METHODS: We used the SEER database to identify patients with TNBC aged between 18 and 45 and randomly classified these patients into a training (n=2,296) and a validation (n=2,297) cohort. Nomograms for estimating overall survival (OS) and breast cancer-specific survival (BCSS) were generated based on multivariate Cox proportional hazards models and competing-risk models in the training cohort. The performances of the nomograms were quantified in the validation cohort using calibration curves, time-dependent receiver operating characteristic (ROC) curves and Harrell's concordance index (C-index). RESULTS: A total of 4,593 TNBC patients of childbearing age were enrolled. Four prognostic factors for OS and six for BCSS were identified and incorporated to construct nomograms. In the validation cohort, calibration curves showed excellent agreement between nomogram-predicted and actual survival data. The nomograms also achieved relatively high Harrell's C-indexes and areas under the time-dependent ROC curves for estimating OS and BCSS in both training and validation cohorts. CONCLUSIONS: Independent prognostic factors were identified, and used to develop nomograms to predict OS and BCSS in childbearing-age patients with TNBC. These models could enable individualized risk estimation and risk-adapted treatment for these patients.
Authors: Carol E DeSantis; Jiemin Ma; Mia M Gaudet; Lisa A Newman; Kimberly D Miller; Ann Goding Sauer; Ahmedin Jemal; Rebecca L Siegel Journal: CA Cancer J Clin Date: 2019-10-02 Impact factor: 508.702
Authors: Matthew E Falagas; Effie A Zarkadoulia; Eleni N Ioannidou; George Peppas; Christos Christodoulou; Petros I Rafailidis Journal: Breast Cancer Res Date: 2007 Impact factor: 6.466