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A repository that contains all the code for the interactive Shiny app of the models developed in our work on predicting response to neoadjuvant treatment.
This project aims to model the disruptive effects of cytotoxic chemotherapeutic drugs on the immunoediting process.
A biologically motivated mathematical formalism is used to estimate the relative risks of breast, lung and thyroid cancers in childhood cancer survivors due to concurrent therapy regimen. This model specifically includes possible organ-specific interaction between radiotherapy and chemotherapy. The model predicts relative risks for developing secondary cancers after chemotherapy in breast, lung and thyroid tissues, and compared with the epidemiological data.
We employed a biologically motivated mathematical model to estimate the radiation and chemotherapy-induced relative risks of thyroid malignancies in four childhood cancer study survivors (CCSS) data sets. the predictions of radiation and chemotherapy-induced relative risks of secondary thyroid malignancies using the mathematical model are compared against four clinical datasets from the CCSS cohort. Moreover, the extracted average value of growth rate of premalignant cells is 0.8175 (per day) and the extracted chemo-induced mutation rate is of the order of 10(−10) (per unit of chemotherapeutic dose).