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.

backgroundThe 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.

objectiveTo predict the survival rate of breast cancer patients at various (0-IV) stages and provide efficient assessment of proposed radiotherapy for patients.

methodsThe 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 exp⁡(-α⁢t) to imply the fundamental degradation of patient's health multiplied by an additional term P⁢(α⁢t), which specifies the recovery effect of a particular therapy.

resultsIts 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-1, 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-1.

conclusionsThe 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.