The current study aimed to evaluate the predictive performance of the American Joint Committee on Cancer eighth edition staging system in patients with invasive breast cancer based on the Surveillance, Epidemiology, and End Results database.Patients diagnosed with T1-2N0M0, estrogen receptor-positive, human epidermal growth factor receptor 2-negative breast cancer from 2010 to 2014 were retrospectively recruited in this analysis. Patients were reassigned to different stages according to the anatomic staging system (AS), prognostic staging system (PS), and prognostic and genomic staging criteria downstaging patients with recurrence score (RS) lower than 11 (PGS_RS11). Cox models were conducted for multivariate analyses, and likelihood ratio (LR) χ, Akaike information criterion (AIC), and Harrell's concordance index (C-index) were calculated for the comparison of different staging systems. Additionally, adjustments were made to generate prognostic and genomic staging criteria downstaging patients with RS lower than 18 (PGS_RS18) and RS lower than 25 (PGS_RS25).PGS_RS11 was an independent predictor for breast cancer-specific survival, as were PS and AS. Adjusted for age and ethnicity, PGS_RS11 (AIC = 2,322.763, C-index = 0.7482, LR χ = 113.17) showed superiority in predicting survival outcomes and discriminating patients compared with AS (AIC = 2,369.132, C-index = 0.6986, LR χ = 60.80) but didn't outperform PS (AIC = 2,320.992, C-index = 0.7487, LR χ = 114.94). The predictive and discriminative ability of PGS_RS18 was the best (AIC = 2297.434, C-index = 0.7828, LR χ = 138.50) when compared with PS and PGS_RS11.PGS_RS11 was superior to AS but comparable with PS in predicting prognosis. Further validations and refinements are needed for the better incorporation of RS into staging systems.Staging systems are of critical importance in informing prognosis and guiding treatment. This study's objective was to evaluate the newly proposed staging system in the American Joint Committee on Cancer eighth edition staging manual, which combined biological and genomic information with the traditional TNM classification for the first time to determine tumor stages of breast cancer. The superiority of the prognostic and genomic staging system was validated in our cohort and possibly could encourage the utility of genomic assays in clinical practice for staging assessment and prognosis prediction.