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      Prediction of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancer

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          Abstract

          Background

          Gastrointestinal (GI) toxicity is a common effect following radiation therapy (RT) for prostate cancer. Purpose of the present work is to compare two Normal Tissue Complication Probability (NTCP) modelling approaches for prediction of late radio-induced GI toxicity after prostate external beam radiotherapy.

          Methods

          The study includes 84 prostate cancer patients evaluated for late rectal toxicity after 3D conformal radiotherapy. Median age was 72 years (range 53-85). All patients received a total dose of 76 Gy to the prostate gland with daily fractions of 2 Gy. The acute and late radio-induced GI complications were classified according to the RTOG/EORTC scoring system. Rectum dose-volume histograms were extracted for Lyman-Kutcher-Burman (LKB) NTCP model fitting using Maximum Likelihood Estimation. The bootstrap method was employed to test the fit robustness. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive power of the LKB and to compare it with a multivariate logistic NTCP model previously determined.

          Results

          At a median follow-up of 36 months, 42% (35/84) of patients experienced grade 1-2 (G1-2) acute GI events while 25% (21/84) of patients developed G1-2 late GI events. The best-estimate of fitting parameters for LKB NTCP model for mild\moderate GI toxicity resulted to be: D 50  = 87.3 Gy, m = 0.37 and n = 0.10. Bootstrap result showed that the parameter fit was robust. The AUC values for the LKB and for the multivariate logistic models were 0.60 and 0.75, respectively.

          Conclusions

          We derived the parameters of the LKB model for mild\moderate GI toxicity prediction and we compared its performance with that of a data-driven multivariate model. Compared to LKB, the multivariate model confirmed a higher predictive power as showed by the AUC values.

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          Most cited references33

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          Radiation dose-volume effects in radiation-induced rectal injury.

          The available dose/volume/outcome data for rectal injury were reviewed. The volume of rectum receiving >or=60 Gy is consistently associated with the risk of Grade >or=2 rectal toxicity or rectal bleeding. Parameters for the Lyman-Kutcher-Burman normal tissue complication probability model from four clinical series are remarkably consistent, suggesting that high doses are predominant in determining the risk of toxicity. The best overall estimates (95% confidence interval) of the Lyman-Kutcher-Burman model parameters are n = 0.09 (0.04-0.14); m = 0.13 (0.10-0.17); and TD(50) = 76.9 (73.7-80.1) Gy. Most of the models of late radiation toxicity come from three-dimensional conformal radiotherapy dose-escalation studies of early-stage prostate cancer. It is possible that intensity-modulated radiotherapy or proton beam dose distributions require modification of these models because of the inherent differences in low and intermediate dose distributions. Copyright 2010 Elsevier Inc. All rights reserved.
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            Reporting and analyzing dose distributions: a concept of equivalent uniform dose.

            Modern treatment planning systems for three-dimensional treatment planning provide three-dimensionally accurate dose distributions for each individual patient. These data open up new possibilities for more precise reporting and analysis of doses actually delivered to irradiated organs and volumes of interest. A new method of summarizing and reporting inhomogeneous dose distributions is reported here. The concept of equivalent uniform dose (EUD) assumes that any two dose distributions are equivalent if they cause the same radiobiological effect. In this paper the EUD concept for tumors is presented, for which the probability of local control is assumed to be determined by the expected number of surviving clonogens, according to Poisson statistics. The EUD can be calculated directly from the dose calculation points or, from the corresponding dose-volume distributions (histograms). The fraction of clonogens surviving a dose of 2 Gy (SF2) is chosen to be the primary operational parameter characterizing radiosensitivity of clonogens. The application of the EUD concept is demonstrated on a clinical dataset. The causes of flattening of the observed dose-response curves become apparent since the EUD concept reveals the finer structure of the analyzed group of patients in respect to the irradiated volumes and doses actually received. Extensions of the basic EUD concept to include nonuniform density of clonogens, dose per fraction effects, repopulation of clonogens, and inhomogeneity of patient population are discussed and compared with the basic formula.
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              Fitting of normal tissue tolerance data to an analytic function.

              During external beam radiotherapy, normal tissues are irradiated along with the tumor. Radiation therapists try to minimize the dose of normal tissues while delivering a high dose to the target volume. Often this is difficult and complications arise due to irradiation of normal tissues. These complications depend not only on the dose but also on volume of the organ irradiated. Lyman has suggested a four-parameter empirical model which can be used to represent normal tissue response under conditions of uniform irradiation to whole and partial volumes as a function of the dose and volume irradiated. In this paper, Lyman's model has been applied to a compilation of clinical tolerance data developed by Emami et al. The four parameters to characterize the tissue response have been determined and graphical representations of the derived probability distributions are presented. The model may, therefore, be used to interpolate clinical data to provide estimated normal tissue complication probabilities for any combination of dose and irradiated volume for the normal tissues and end points considered.
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                Author and article information

                Contributors
                vittoria.davino@ibb.cnr.it
                giuseppe.palma@ibb.cnr.it
                raffaele.liuzzi@cnr.it
                m.conson@gmail.com
                Francydoria@libero.it
                marsalva@unina.it
                roberto.pacelli@unina.it
                laura.cella@cnr.it
                Journal
                Radiat Oncol
                Radiat Oncol
                Radiation Oncology (London, England)
                BioMed Central (London )
                1748-717X
                8 April 2015
                8 April 2015
                2015
                : 10
                : 80
                Affiliations
                [ ]Institute of Biostructure and Bioimaging, National Council of Research (CNR), Naples, Italy
                [ ]Department of Advanced Biomedical Sciences, Federico II University School of Medicine, Naples, Italy
                Article
                389
                10.1186/s13014-015-0389-5
                4404272
                25890376
                83bac305-075c-442f-a86d-b7b8e347f5cd
                © D'Avino et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 October 2014
                : 25 March 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Oncology & Radiotherapy
                ntcp,radiation induced rectum toxicity,lkb model,multivariate model
                Oncology & Radiotherapy
                ntcp, radiation induced rectum toxicity, lkb model, multivariate model

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