Applying decision trees to establish risk rating model of breast cancer incidence based on non-genetic factors among Southwest China females

• Published in: Zhōnghuá zhŏngliú zázhì Vol. 40; no. 11; pp. 872 - 877
• Main Authors: Li, Q, Diao, S, Li, H, He, H, Li, J Y
• Format: Journal Article
• Language: Chinese
• Published: China 23.11.2018
• Subjects: Models, statistical; Decision trees; Breast neoplasms
• ISSN: 0253-3766
• DOI: 10.3760/cma.j.issn.0253-3766.2018.11.015

To estimate incident probability and establish risk rating model of breast cancer incidence under different combinations of non-genetic factors among Southwest China females, applying the decision trees. From 2014 to 2015, a total of 783 cases, which were pathologically diagnosed as primary breast cancer, were sequentially collected from West China Hospital of Sichuan University, Sichuan Cancer Hospital and Sichuan Province People's Hospital. 3, 879(excluding 36 samples with missing data) controls were randomly selected and matched by area of residence and age. Classification and regression tree (CART) algorithm was applied to construct breast cancer risk rating model according to non-genetic factors. 5 test sets were randomly selected for model validation. BI-RADS classes, menopausal status, age, history of benign breast disease, menarche age, age of first delivery and number of live births were identified as risk factors and included in the risk rating model of breast cancer incidence. Among these factors, BI-RADS classes, menopausal status and age were the most important. The risk rating model developed were vitrificated by 5 test sets, and the average sensitivity, positive predictive value, accuracy were 95.60%, 92.26%, 97.93%, respectively. Breast cancer risk rating model constructed by decision trees was valid and reliable. The model could be used as the basic tool of breast cancer risk assessment among Southwest China females.