BACKGROUND: @entity137 of the respiratory system is quite common after radiotherapy of @entity5 ; @entity0 @entity1 represent one of the groups for which there is also a long expected survival. The quantification of lung tissue response to irradiation is important in designing treatments associated with a minimum of complications and maximum @entity5 control. METHODS: The study population consisted of 68 @entity1 who received irradiation for @entity0 at Stage II. @entity1207 was retrospectively assessed on the basis of clinical symptoms and radiological findings. For each @entity1 , a measure of the exposure (i.e., the lung dose-volume histogram [DVH]) and a measure of the outcome was available. Based on these data, a maximum likelihood fitting to the relative seriality model was performed. The uncertainties of the model parameters were calculated and their impact on the dose-response curve was studied. The optimum parameter set was then applied to 5 other @entity1 groups treated for @entity0 , and the normal tissue complication probability (NTCP) was calculated. Each group was individuated by the radiotherapy treatment technique used; the dose distribution in the lung was described by a mean DVH and the incidence of @entity1207 in each group was known. Lung radiosensitivity was assumed to be homogeneous through all of the calculations. RESULTS: The relative seriality model could describe the dataset. The volume effect was found to be relevant in the description of @entity1207 . Age was found to be associated with increased risk of @entity1207 . Two distinct dose-response curves were obtained by splitting the group according to age. The impact of the parameter uncertainties on the dose-response curve was quite large. The parameter set determined could be used predictively on 3 of the 5 @entity1 groups. CONCLUSION: The complication data could be modeled with the relative seriality model. However, further independent datasets, classified according to the same endpoint, must be analyzed before introducing NTCP modeling in clinical practice.

@entity1207 after XXXX irradiation: analysis of the complication probability using the relative seriality model.

@entity1 :: ('9606', 'Species') :: ['patients', 'patient'] @entity137 :: ('MESH:D064420', 'Disease') :: ['Toxicity'] @entity0 :: ('MESH:D001943', 'Disease') :: ['breast cancer'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'thoracic tumors'] @entity1207 :: ('MESH:D017564', 'Disease') :: ['radiation pneumonitis', 'Radiation pneumonitis']
@entity0 :: (MESH:D001943,Disease) :: ['breast cancer']
