Predicting the need for adaptive radiotherapy in head and neck cancer

Brown, Elizabeth, Owen, Rebecca, Harden, Fiona, Mengersen, Kerrie, Oestreich, Kimberley, Houghton, Whitney, Poulsen, Michael, Harris, Selina, Lin, Charles, & Porceddu, Sandro (2015) Predicting the need for adaptive radiotherapy in head and neck cancer. Radiotherapy & Oncology, 116(1), pp. 57-63.

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Abstract

Background and purpose

  • 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.

Materials and 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.

Conclusion

  • 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.

Impact and interest:

9 citations in Scopus
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9 citations in Web of Science®

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ID Code: 86062
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: head and neck cancer, radiotherapy, adaptive, IMRT, VMAT, Tomotherapy
DOI: 10.1016/j.radonc.2015.06.025
ISSN: 1879-0887
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > ONCOLOGY AND CARCINOGENESIS (111200) > Radiation Therapy (111208)
Divisions: Current > Research Centres > ARC Centre of Excellence for Mathematical & Statistical Frontiers (ACEMS)
Current > Schools > School of Clinical Sciences
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Elsevier Ireland Ltd.
Deposited On: 28 Jul 2015 23:17
Last Modified: 09 Aug 2016 09:09

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