Affiliation:
1. Faculty of Life Science and Biopharmaceutics Shenyang Pharmaceutical University Shenyang China
2. School of Medical Devices Shenyang Pharmaceutical University Shenyang China
3. Liaoning Professional Technology Innovation Center on Medical Big Data and Artificial Intelligence Shenyang China
4. Department of Clinical Pharmacy Shenyang Pharmaceutical University Shenyang China
Abstract
AbstractThis study aimed to investigate the risk factors for the onset of subsequent primary breast cancer (SPBC) in women with a previous diagnosis of early‐stage breast cancer (BC) and to construct a prognostic prediction model for patients with SPBC. Using the Surveillance, Epidemiology, and End Results‐17 (SEER‐17) database, we conducted a retrospective cohort analysis on women with initial primary early‐stage BC from 2004 to 2015. Standardized incidence ratio (SIR) was calculated to determine the risk of subsequent primary cancer (SPC). A competing risk model was built to identify the risk factors for the onset of SPBC. And risk factors associated with breast cancer‐specific mortality in SPBC patients were evaluated and presented in the form of nomogram. Compared with the general population, the overall risk of SPC for all sites was significantly elevated in women with early‐stage BC (SIR = 1.21, 95% CI: 1.20–1.23), and breast is the most frequent site. Age, race and ethnicity, year of diagnosis, history of other tumors, histological type, surgery, radiation, chemotherapy, tumor size, positive lymph nodes numbers and ER status were independent risk factors (p < .05) for the onset of SPBC. A new prognosis nomogram demonstrated good discrimination after internal validation with a C‐index of 0.869 (95% CI: 0.859–0.880), and showed favorable consistency and clinical usefulness. The incidence of SPBC and prognosis of patients with SPBC were well estimated based on a large cohort. Our nomogram model had excellent prediction performance and could be a useful tool to predict prognosis.