Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents

Cancer Communications

Hon-Yi Shi¹  Joon-Khim Loh²  Su-Hsin Huang³  Ming-Feng Houg⁴  Jinn-Tsong Tsai⁵ 

[1] Department of Computer Science, National Pingtung University, Pingtung, China;Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, China;Department of Nursing, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, China;Department of Surgery, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, China;Divison of Neurosurgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung, China

关键词: Breast cancer surgery;    Artificial neural networks;    Multiple logistic regression;    Cox regression;    5-year mortality;   

DOI  :  10.1186/s40880-017-0192-9

学科分类：肿瘤学

来源: Springer

【 摘 要 】

Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast cancer patients after surgery and compare predictive accuracy between the ANN model, multiple logistic regression (MLR) model, and Cox regression model. This study compared the MLR, Cox, and ANN models based on clinical data of 3632 breast cancer patients who underwent surgery between 1996 and 2010. An estimation dataset was used to train the model, and a validation dataset was used to evaluate model performance. The sensitivity analysis was also used to assess the relative significance of input variables in the prediction model. The ANN model significantly outperformed the MLR and Cox models in predicting 5-year mortality, with higher overall performance indices. The results indicated that the 5-year postoperative mortality of breast cancer patients was significantly associated with age, Charlson comorbidity index (CCI), chemotherapy, radiotherapy, hormone therapy, and breast cancer surgery volumes of hospital and surgeon (all P < 0.05). Breast cancer surgery volume of surgeon was the most influential (sensitive) variable affecting 5-year mortality, followed by breast cancer surgery volume of hospital, age, and CCI. Compared with the conventional MLR and Cox models, the ANN model was more accurate in predicting 5-year mortality of breast cancer patients who underwent surgery. The mortality predictors identified in this study can also be used to educate candidates for breast cancer surgery with respect to the course of recovery and health outcomes.

【 授权许可】

CC BY