Abstract
Background: Targeted therapies have largely improved prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. Yet, disease can still progress rapidly for some patients in the first two years after diagnosis. Our study aimed to establish a nomogram model to predict the 2-year breast cancer-specific survival (BCSS) in early HER2-positive breast cancer patients. Methods: A total of 32,481 HER2-positive patients derived from Surveillance, Epidemiology, and End Results (SEER) database were included in the construction of nomogram. Concordance index (C-index) and calibration curve were used to evaluate the discrimination ability and predictive accuracy. We tested the model in 804 patients from Shanghai Jiao Tong University Breast Cancer Data Base (SJTU-BCDB). Results: Age, estrogen receptor (ER) status, progesterone receptor (PR) status, histologic type, T stage and N stage were selected to construct the nomogram according to multivariable analysis. The 2-year BCSS rate was 95% and 60% for patients at low risk (<8 points) and high risk (>13 points) respectively. The C-index of model derived from SEER database is 0.81 (95%CI 0.79-0.83). Sensitivity analysis was performed in patients after breast surgeries with the C-index of 0.81 (95%CI, 0.79-0.83). Validation in 804 patients from SJTU-BCDB showed respective C-index of 0.77 (95%CI, 0.62-0.92) in total population, 0.67 (95%CI 0.44-0.90) and 0.90 (95%CI 0.81-0.90) in patients who received anti-HER2 therapy or not. Discussion: The novel nomogram can predict the 2-year survival outcome in HER2-positive patients independent of receiving anti-HER2 therapy or not and allow clinicians to adjust therapeutic strategies for patients with higher risk.
A Novel Prognostic Nomogram for the 2-year Survival in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer Patients
