Abstract
AimsA normal tissue complication probability (NTCP) model of severe acute mucositis would be highly useful to guide clinical decision making and inform radiotherapy planning. We aimed to improve upon our previous model by using a novel oral mucosal surface organ at risk (OAR) in place of an oral cavity OAR. Materials and methodsPredictive models of severe acute mucositis were generated using radiotherapy dose to the oral cavity OAR or mucosal surface OAR and clinical data. Penalised logistic regression and random forest classification (RFC) models were generated for both OARs and compared. Internal validation was carried out with 100-iteration stratified shuffle split cross-validation, using multiple metrics to assess different aspects of model performance. Associations between treatment covariates and severe mucositis were explored using RFC feature importance. ResultsPenalised logistic regression and RFC models using the oral cavity OAR performed at least as well as the models using mucosal surface OAR. Associations between dose metrics and severe mucositis were similar between the mucosal surface and oral cavity models. The volumes of oral cavity or mucosal surface receiving intermediate and high doses were most strongly associated with severe mucositis. ConclusionsThe simpler oral cavity OAR should be preferred over the mucosal surface OAR for NTCP modelling of severe mucositis. We recommend minimising the volume of mucosa receiving intermediate and high doses, where possible.
Highlights
Mucositis is a common and important acute toxicity of head and neck radiotherapy, which may result in pain, dysphagia [1] and weight loss, and, reduced quality of life [2,3]
For all models the use of the mucosal surface contours (MSC)-PM organ at risk (OAR) did not lead to an improvement in predictive performance compared with the corresponding model using the oral cavity volume contours (OCC)-PM OAR
For both structures (OCC-PM and MSC-PM) and both types of model (PLR and random forest classification (RFC)), the addition of the spatial dose metrics did not result in improved model performance, as assessed by any of the metrics
Summary
Mucositis is a common and important acute toxicity of head and neck radiotherapy, which may result in pain, dysphagia [1] and weight loss, and, reduced quality of life [2,3]. Mucositis may lead to missed treatment fractions [4] and is frequently dose limiting in dose-escalation and accelerated fractionation regimens designed to improve tumour control [5e7]. Severe acute reactions have been implicated in the subsequent development of ‘late’ radiation toxicity [8e10]. Author for correspondence: J.A. Dean, Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG, UK.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
