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Volume effects of late term normal tissue toxicity in prostate cancer radiotherapy.

机译:前列腺癌放疗中晚期正常组织毒性的体积效应。

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Modeling of volume effects for treatment toxicity is paramount for optimization of radiation therapy.; This thesis proposes a new model for calculating volume effects in gastro-intestinal and genito-urinary normal tissue complication probability (NTCP) following radiation therapy for prostate carcinoma.; The radiobiological and the pathological basis for this model and its relationship to other models are detailed. A review of the radiobiological experiments and published clinical data identified salient features and specific properties a biologically adequate model has to conform to.; The new model was fit to a set of actual clinical data. In order to verify the goodness of fit, two established NTCP models and a non-NTCP measure for complication risk were fitted to the same clinical data.; The method of fit for the model parameters was maximum likelihood estimation. Within the framework of the maximum likelihood approach I estimated the parameter uncertainties for each complication prediction model. The quality-of-fit was determined using the Aikaike Information Criterion. Based on the model that provided the best fit, I identified the volume effects for both types of toxicities. Computer-based bootstrap resampling of the original dataset was used to estimate the bias and variance for the fitted parameter values.; Computer simulation was also used to estimate the population size that generates a specific uncertainty level (3%) in the value of predicted complication probability. The same method was used to estimate the size of the patient population needed for accurate choice of the model underlying the NTCP.; The results indicate that, depending on the number of parameters of a specific NTCP model, 100 (for two parameter models) and 500 patients (for three parameter models) are needed for accurate parameter fit.; Correlation of complication occurrence in patients was also investigated. The results suggest that complication outcomes are correlated in a patient, although the correlation coefficient is rather small.
机译:对于治疗毒性的体积效应建模对于优化放射治疗至关重要。本文提出了一种新的模型,用于计算前列腺癌放射治疗后胃肠道和生殖泌尿正常组织并发症概率(NTCP)的体积效应。详细介绍了该模型的放射生物学和病理学基础,以及与其他模型的关系。回顾放射生物学实验和发表的临床数据,确定了生物学上适当的模型必须符合的显着特征和特定特性。新模型适合一组实际临床数据。为了验证拟合的良​​好性,将两个已建立的NTCP模型和一个用于并发症风险的非NTCP量度拟合到同一临床数据。模型参数的拟合方法是最大似然估计。在最大似然方法的框架内,我估计了每种并发症预测模型的参数不确定性。拟合质量是使用Aikaike信息准则确定的。基于提供最佳拟合的模型,我确定了两种毒性的体积效应。原始数据集的基于计算机的自举重采样用于估计拟合参数值的偏差和方差。还使用计算机模拟来估计人口规模,该人口规模在预测并发症发生率的值中产生特定的不确定性水平(3%)。使用相同的方法来估算准确选择NTCP模型所需的患者人数。结果表明,根据特定NTCP模型的参数数量,需要100位(用于两个参数模型)和500位患者(用于三个参数模型)以进行准确的参数拟合。还研究了患者并发症发生的相关性。结果表明,尽管患者的并发症相关系数很小,但其并发症结局与患者相关。

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