title: Predicting the need for adaptive radiotherapy in head and neck cancer.
abstract: OBJECTIVE
  Adaptive radiotherapy (ART) can account for the dosimetric impact of anatomical change in head and neck cancer patients; however it can be resource intensive. Consequently, it is imperative that patients likely to require ART are identified. The purpose of this study was to find predictive factors that identify oropharyngeal squamous cell carcinoma (OPC) and nasopharyngeal carcinoma (NPC) patients more likely to need ART.
  
  
  METHODS
  One hundred and ten patients with OPC or NPC were analysed. Patient demographics and tumour characteristics were compared between patients who were replanned and those that were not. Factors found to be significant were included in logistic regression models. Risk profiles were developed from these models. A dosimetric analysis was performed.
  
  
  RESULTS
  Nodal disease stage, pre-treatment largest involved node size, diagnosis and initial weight (categorised in 2 groups) were identified as significant for inclusion in the model. Two models were found to be significant (p=0.001), correctly classifying 98.2% and 96.1% of patients respectively. Three ART risk profiles were developed.
  
  
  CONCLUSIONS
  Predictive factors identifying OPC or NPC patients more likely to require ART were reported. A risk profile approach could facilitate the effective implementation of ART into radiotherapy departments through forward planning and appropriate resource allocation.
authors.affiliation: Radiation Oncology Department, Princess Alexandra Hospital, Brisbane, Australia; Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, Australia. Electronic address: Elizabeth.Brown3@health.qld.gov.au.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Brown
authors.affiliation: Radiation Oncology Department, Radiation Oncology Mater Centre, Brisbane, Australia.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Owen
authors.affiliation: Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, Australia.
authors.forename: Fiona
authors.initials: F
authors.lastname: Harden
authors.affiliation: Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, Australia.
authors.forename: Kerrie
authors.initials: K
authors.lastname: Mengersen
authors.affiliation: Radiation Oncology Department, Princess Alexandra Hospital, Brisbane, Australia.
authors.forename: Kimberley
authors.initials: K
authors.lastname: Oestreich
authors.affiliation: Radiation Oncology Department, Radiation Oncology Mater Centre, Brisbane, Australia.
authors.forename: Whitney
authors.initials: W
authors.lastname: Houghton
authors.affiliation: Radiation Oncology Department, Radiation Oncology Mater Centre, Brisbane, Australia.
authors.forename: Michael
authors.initials: M
authors.lastname: Poulsen
authors.affiliation: Radiation Oncology Department, Royal Brisbane and Women's Hospital, Australia.
authors.forename: Selina
authors.initials: S
authors.lastname: Harris
authors.affiliation: Radiation Oncology Department, Royal Brisbane and Women's Hospital, Australia.
authors.forename: Charles
authors.initials: C
authors.lastname: Lin
authors.affiliation: Radiation Oncology Department, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Brisbane, Australia.
authors.forename: Sandro
authors.initials: S
authors.lastname: Porceddu
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D006258:Head and Neck Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D011874:Radiometry; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted; D014057:Tomography, X-Ray Computed
keywords: Adaptive; Head and neck cancer; IMRT; Radiotherapy; Tomotherapy; VMAT