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Erschienen in:
17.04.2017 | Brief Report
Assessment of the prognostic and discriminating value of the novel bioscore system for breast cancer; a SEER database analysis
Erschienen in: Breast Cancer Research and Treatment | Ausgabe 1/2017
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Background
An updated bioscore has been proposed within the context of the 8th edition American Joint Committee on Cancer (AJCC) staging system for breast cancer. This study seeks to validate the discriminating value of this bioscore among non-metastatic breast cancer patients registered within the surveillance, epidemiology, and end results (SEER) database.
Methods
Through SEER*Stat program, SEER database (2010–2013) was accessed and bioscore was formulated for each patient. Overall and cancer-specific survival analyses according to both bioscore and AJCC pathological stages were conducted through Kaplan–Meier analysis/log-rank testing, and multivariate analysis was conducted through a Cox proportional model.
Results
A total of 181030 patients with non-metastatic, surgically treated breast cancer were identified in the period from 2010 to 2013. For overall and cancer-specific survival assessment according to the bioscore system, P values for pairwise comparisons among different score points were significant (P < 0.0001) except for the comparison between score 0 and score 1. For cancer-specific survival assessment according to the AJCC stages, P values for pairwise comparisons among different stages were significant (P < 0.0001) except for the comparison between stages IIIB and IIIC. For overall survival assessment according to the AJCC stages, P values for pairwise comparisons among different stages were significant (P < 0.001) except for the comparison between stages IA and IB. In a multivariate analysis, the following factors were associated with better cancer-specific survival (earlier stage disease, ER positivity, PR positivity, Her2 neu positivity, and nuclear grade) (P < 0.0001).
Conclusion
The current analysis confirms the prognostic utility of the bioscore system and suggests it may be incorporated into decision-making algorithms for non-metastatic breast cancer.