Survival rate prediction of breast cancer patients of 0-IV stages with and without radiotherapy via a revised Taylor series expansion algorithm: A population-based study in Taiwan

BACKGROUND: The morbidity of breast cancer has continuously achieved a global topicality. In particular, during the last decade several ten thousand female adults in Taiwan have been confirmed as breast cancer patients. OBJECTIVE: To predict the survival rate of breast cancer patients at various (0-IV) stages and provide efficient assessment of proposed radiotherapy for patients. METHODS: The prediction algorithm proposed is based on the revised hit and target model and implies the application of Taylor series expansion to the population-based survey dataset. The proposed algorithm features a specific function comprising a single simple exponential term [Formula: see text] to imply the fundamental degradation of patient’s health multiplied by an additional term [Formula: see text] , which specifies the recovery effect of a particular therapy. RESULTS: Its calculated values for breast cancer patients who undergone radiotherapy at different stages 0-IV were {0.0029, 0.0066, 0.0178, 0.0475, 0.1785} yr [Formula: see text] , respectively, while those for corresponding groups of patients with no radiotherapy were assessed as {0.0072, 0.0137, 0.0264, 0.0913, 0.2425} yr [Formula: see text]. CONCLUSIONS: The revised algorithm successfully interpreted the breast cancer patients’ survival rate at stages 0-IV and evaluated the necessity of radiotherapy for patients at various stages as well.