Modeling Acute Urinary Toxicity After Radiotherapy For Prostate Cancer.

156 Background: DUE-01 is a multi-centric observational study aimed at developing predictive models of genito-urinary toxicity and erectile dysfunction for prostate cancer patients treated with conventional (1.8-2Gy/fr, CONV) or moderate hypofractionation (2.5-2.7Gy/fr, HYPO). Current analysis focused on modelling the relationship between the risk of IPSS≥15 (IPSS15end) at the end of radiotherapy and clinincal/dosimetric risk factors. Methods: Planning data and relevant clinical factors were prospectively collected, including DVH/DSH referred to the whole treatment and to the weekly delivered dose (DVHw/DSHw). Best discriminating DVH/DSH parameters were selected by the differences between patients with/without IPSS15end=1 (t-test). Bootstrap variable selection techniques (300 resamples) in the framework of logistic backward feature selection was used to improve model building (El Naqa, IJROBP 2006). Graphical and quantitative analyses of the variable selection process applied to bootstrap data replicates was used to avoid underfitting/overfitting and to assess the final multivariable model. Results: 247 patients were available (CONV:116, HYPO:131). Seventy one out of 247 (28.7%) reported IPSS15end=1. The most predictive dosimetric tools were the absolute weekly delivered dose (DSHw and DVHw). DSHw and DVHw were alternatively inserted in the bootstrap variable selection flow, together with clinical risk factors. Due to the number of events, a logistic model containing six variables was accepted On the basis of observed frequency of variables in the top six positions, a model including basal IPSS (median OR=1.22, p=0.00001), use of anti-hypertensives (median OR=2.7, p=0.01), absolute bladder surface receiving more than 10.5 Gy/week (s10.5w, median OR=1.16, p=0.0001), and s12.5w (median OR=1.07, p=0.005), was choosen. AUC of this model was 0.80. Silmilar results were obtained when using DVHw. Conclusions: Basal IPSS, use of anti-hypertensive drugs, s10.5w/v10.5w and s12.5w/v12.5w are the main predictors of IPSS>=15 at the end of radiotherapy Bootstrap variable selection technique gives the modeler more insight into the importance and stability of the different variables selected and allows development of more robust models