title: Normal Tissue Complication Probability (NTCP) Modelling of Severe Acute Mucositis using a Novel Oral Mucosal Surface Organ at Risk.
abstract: A 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.
  
  
  
  Predictive 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.
  
  
  
  Penalised 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.
  
  
  
  The 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.
authors.affiliation: Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK. Electronic address: jamie.dean@icr.ac.uk.
authors.forename: J A
authors.initials: JA
authors.lastname: Dean
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: L C
authors.initials: LC
authors.lastname: Welsh
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: K H
authors.initials: KH
authors.lastname: Wong
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: A
authors.initials: A
authors.lastname: Aleksic
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: E
authors.initials: E
authors.lastname: Dunne
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: M R
authors.initials: MR
authors.lastname: Islam
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: A
authors.initials: A
authors.lastname: Patel
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: P
authors.initials: P
authors.lastname: Patel
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: I
authors.initials: I
authors.lastname: Petkar
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: I
authors.initials: I
authors.lastname: Phillips
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: J
authors.initials: J
authors.lastname: Sham
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: U
authors.initials: U
authors.lastname: Schick
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
authors.forename: K L
authors.initials: KL
authors.lastname: Newbold
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
authors.forename: S A
authors.initials: SA
authors.lastname: Bhide
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
authors.forename: K J
authors.initials: KJ
authors.lastname: Harrington
authors.affiliation: Head and Neck Unit, The Royal Marsden NHS Foundation Trust, London, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.
authors.forename: C M
authors.initials: CM
authors.lastname: Nutting
authors.affiliation: Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK.
authors.forename: S L
authors.initials: SL
authors.lastname: Gulliford
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D008954:Models, Biological; D009061:Mouth Mucosa / Q000528:radiation effects*; D052016:Mucositis / Q000209:etiology*; D011336:Probability; D011878:Radiotherapy / Q000009:adverse effects* / Q000379:methods; D011879:Radiotherapy Dosage; D015203:Reproducibility of Results; D055815:Young Adult
keywords: Head and neck radiotherapy; NTCP modelling; OAR delineation; machine learning; mucositis; oral mucosa