Abstract
BackgroundConsidering the lack of efficient breast cancer prediction models suitable for general population screening in China. We aimed to develop a risk prediction model to identify high-risk populations, to help with primary prevention of breast cancer among Han Chinese women.MethodsA cause-specific competing risk model was used to develop the Han Chinese Breast Cancer Prediction model. Data from the Shandong Case-Control Study (328 cases and 656 controls) and Taixing Prospective Cohort Study (13,176 participants) were used to develop and validate the model. The expected/observed (E/O) ratio and C-statistic were calculated to evaluate calibration and discriminative accuracy of the model, respectively.ResultsCompared with the reference level, the relative risks (RRs) for highest level of number of abortions, age at first live birth, history of benign breast disease, body mass index (BMI), family history of breast cancer, and life satisfaction scores were 6.3, 3.6, 4.3, 1.9, 3.3, 2.4, respectively. The model showed good calibration and discriminatory accuracy with an E/O ratio of 1.03 and C-statistic of 0.64.ConclusionsWe developed a risk prediction model including fertility status and relevant disease history, as well as other modifiable risk factors. The model demonstrated good calibration and discrimination ability.
Highlights
Considering the lack of efficient breast cancer prediction models suitable for general population screening in China
Competing risks are said to be present when an individual is at risk for more than one mutually exclusive event, such as death from a different cause, and the occurrence of one of these competing events will prevent the event of interest from ever happening
Several risk prediction models have been developed in Western countries; the two most widely used are the Gail cause-specific hazard model with traditional risk factors as predictors [4], and the International Breast Cancer Intervention Study (IBIS)model, which includes genetic markers [5]
Summary
Considering the lack of efficient breast cancer prediction models suitable for general population screening in China. We aimed to develop a risk prediction model to identify high-risk populations, to help with primary prevention of breast cancer among Han Chinese women. Considering the limited medical resources, especially in rural areas of China, a risk prediction model that is suitable for general population screening is urgently needed. Gail proposed a method to estimate individual probabilities of developing breast cancer, based on a cause-specific hazard model [4]. Several risk prediction models have been developed in Western countries; the two most widely used are the Gail cause-specific hazard model with traditional risk factors as predictors [4], and the International Breast Cancer Intervention Study (IBIS)model, which includes genetic markers [5]. The Gail II model was developed based on the Gail model and provides a feasible web-based instrument [6]; that model was first developed in a Caucasian ethnic
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
