Research Paper Volume 12, Issue 19 pp 19628—19640
Risk factors and prediction of second primary cancer in primary female non-metastatic breast cancer survivors
- 1 Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety and Collaborative Innovation Center of Social Risks Governance in Health, Fudan University, Shanghai, China
- 2 Clinical Research Center, Shanghai General Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China
Received: June 10, 2020 Accepted: August 1, 2020 Published: October 13, 2020
https://doi.org/10.18632/aging.103939How to Cite
Copyright: © 2020 Qian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
This study aimed to investigate the risk factors of second primary cancer among female breast cancer (BC) survivors, with emphasis on the prediction of the individual risk conditioned on the patient’s characteristics. We identified 208,474 BC patients diagnosed between 2004 and 2010 from the Surveillance, Epidemiology and End Results (SEER) database. Subdistribution proportional hazard model and competing-risk nomogram were used to explore the risk factors of second primary BC and non-BC, and to predict the 5- and 10-year probabilities of second primary BC. Model performance was evaluated via calibration curves and decision curve analysis. The overall 3-, 5-, and 10-year cumulative incidences for second primary BC were 0.9%, 1.6% and 4.4%, and for second primary non-BC were 2.3%, 3.9%, and 7.8%, respectively. Age over 70 years at diagnosis, black race, tumor size over 2 cm, negative hormone receptor, mixed histology, localized tumor, lumpectomy alone, and surgeries plus radiotherapy were significantly associated with increased risk of second BC. The risk of second non-BC was only related to age, race and tumor size. The proposed risk model as well as its nomogram was clinically beneficial to identify patients at high risk of developing second primary breast cancer.
Abbreviations
BC: female breast cancer; SPC: second primary cancer; SIR: standard incidence ratio; SEER: Surveillance: Epidemiology: and End Results Program; HR: hormone receptor; ER: estrogen receptor; PR: progesterone receptor; CIF: cumulative incidence function; sHR: subdistribution hazard ratio; DCA: decision curve analysis.