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 and Porceddu, Sandro (2015) Predicting the need for adaptive radiotherapy in head and neck cancer. Radiotherapy and Oncology, 116 1: 57-63. doi:10.1016/j.radonc.2015.06.025

Author Brown, Elizabeth
Owen, Rebecca
Harden, Fiona
Mengersen, Kerrie
Oestreich, Kimberley
Houghton, Whitney
Poulsen, Michael
Harris, Selina
Lin, Charles
Porceddu, Sandro
Title Predicting the need for adaptive radiotherapy in head and neck cancer
Journal name Radiotherapy and Oncology   Check publisher's open access policy
ISSN 1879-0887
Publication date 2015-07
Sub-type Article (original research)
DOI 10.1016/j.radonc.2015.06.025
Open Access Status Not yet assessed
Volume 116
Issue 1
Start page 57
End page 63
Total pages 7
Place of publication Shannon, Clare, Ireland
Publisher Elsevier Ireland
Collection year 2016
Language eng
Formatted 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.
Keyword Adaptive
Head and neck cancer
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Medicine Publications
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