Generalized monotonic functional mixed models with application to modelling normal tissue complications |
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Authors: | Matthew Schipper Jeremy M. G. Taylor Xihong Lin |
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Affiliation: | Innovative Analytics, Kalamazoo, USA; University of Michigan, Ann Arbor, USA; Harvard School of Public Health, Boston, USA |
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Abstract: | Summary. Normal tissue complications are a common side effect of radiation therapy. They are the consequence of the dose of radiation that is received by the normal tissue surrounding the site of the tumour. Within a specified organ each voxel receives a certain dose of radiation, leading to a distribution of doses over the organ. It is often not known what aspect of the dose distribution drives the presence and severity of the complications. A summary measure of the dose distribution can be obtained by integrating a weighting function of dose ( w ( d )) over the density of dose. For biological reasons the weight function should be monotonic. We propose a generalized monotonic functional mixed model to study the dose effect on a clinical outcome by estimating this weight function non-parametrically by using splines and subject to the monotonicity constraint, while allowing for overdispersion and correlation of multiple obervations within the same subject. We illustrate our method with data from a head and neck cancer study in which the irradiation of the parotid gland results in loss of saliva flow. |
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Keywords: | Dose effect Functional data Monotonicity Non-parametric regression Normal tissue complications Overdispersion Splines |
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