Predicting the need for adaptive radiotherapy in XXXX .

@entity1 @entity135 @entity66 @entity5 @entity957 @entity189
BACKGROUND AND PURPOSE: Adaptive radiotherapy (ART) can account for the dosimetric impact of anatomical change in @entity135 @entity1 ; however it can be resource intensive. Consequently, it is imperative that @entity1 likely to require ART are identified. The purpose of this study was to find predictive factors that identify @entity957 ( @entity957 ) and @entity189 ( @entity189 ) @entity1 more likely to need ART. MATERIALS AND METHODS: One hundred and ten @entity1 with @entity957 or @entity189 were analysed. @entity1 @entity5 characteristics were compared between @entity1 who were replanned and those that were not. Factors found to be significant were included in logistic regression models. Risk profiles were developed from these models. A dosimetric analysis was performed. RESULTS: @entity66 stage, pre-treatment largest involved node size, diagnosis and initial weight (categorised in 2 groups) were identified as significant for inclusion in the model. Two models were found to be significant (p=0.001), correctly classifying 98.2% and 96.1% of @entity1 respectively. Three ART risk profiles were developed. CONCLUSION: Predictive factors identifying @entity957 or @entity189 @entity1 more likely to require ART were reported. A risk profile approach could facilitate the effective implementation of ART into radiotherapy departments through forward planning and appropriate resource allocation.
