PURPOSE: To create, on the basis of available data, a mathematical model to describe the tumor stage- and field size-dependent risks/benefits of postoperative radiotherapy (PORT) for non-small-cell lung cancer (NSCLC), and to assess whether this simple model can accurately describe the reported changes in overall survival. METHODS AND MATERIALS: The increase in overall survival afforded by PORT is assumed equal to the increase in cancer-specific survival minus the rate of RT-induced mortality. The increase in cancer-specific survival is the product of the probabilities of (residual local disease) x (sterilization of residual disease with PORT) x (absence of metastatic disease). Data were extracted from the literature to estimate these probabilities. Different models were considered to relate the RT-induced mortality to field size. RESULTS: The rate of RT-induced mortality seems to be proportional to the cube of the field size. When these mortality rates are included in the model, the predicted changes in overall survival approximate the literature values. CONCLUSION: Clinical data can be explained by a simple model that suggests that RT-induced mortality is strongly dependent on field size and at least partly offsets the benefit afforded by PORT. Smaller RT fields, tailored to treat the areas most at risk for recurrence, provide the highest therapeutic ratio. The data used do not reflect the impact of chemotherapy, which will reduce the rate of distant metastases and enhance the efficacy of RT.
PURPOSE: To create, on the basis of available data, a mathematical model to describe the tumor stage- and field size-dependent risks/benefits of postoperative radiotherapy (PORT) for non-small-cell lung cancer (NSCLC), and to assess whether this simple model can accurately describe the reported changes in overall survival. METHODS AND MATERIALS: The increase in overall survival afforded by PORT is assumed equal to the increase in cancer-specific survival minus the rate of RT-induced mortality. The increase in cancer-specific survival is the product of the probabilities of (residual local disease) x (sterilization of residual disease with PORT) x (absence of metastatic disease). Data were extracted from the literature to estimate these probabilities. Different models were considered to relate the RT-induced mortality to field size. RESULTS: The rate of RT-induced mortality seems to be proportional to the cube of the field size. When these mortality rates are included in the model, the predicted changes in overall survival approximate the literature values. CONCLUSION: Clinical data can be explained by a simple model that suggests that RT-induced mortality is strongly dependent on field size and at least partly offsets the benefit afforded by PORT. Smaller RT fields, tailored to treat the areas most at risk for recurrence, provide the highest therapeutic ratio. The data used do not reflect the impact of chemotherapy, which will reduce the rate of distant metastases and enhance the efficacy of RT.
Authors: Cliff G Robinson; Aalok P Patel; Jeffrey D Bradley; Todd DeWees; Saiama N Waqar; Daniel Morgensztern; Maria Q Baggstrom; Ramaswamy Govindan; Jennifer M Bell; Tracey J Guthrie; Graham A Colditz; Traves D Crabtree; Daniel Kreisel; Alexander S Krupnick; G Alexander Patterson; Bryan F Meyers; Varun Puri Journal: J Clin Oncol Date: 2015-02-09 Impact factor: 44.544
Authors: John L Mikell; Theresa W Gillespie; William A Hall; Dana C Nickleach; Yuan Liu; Joseph Lipscomb; Suresh S Ramalingam; Raj S Rajpara; Seth D Force; Felix G Fernandez; Taofeek K Owonikoko; Rathi N Pillai; Fadlo R Khuri; Walter J Curran; Kristin A Higgins Journal: J Thorac Oncol Date: 2015-03 Impact factor: 15.609