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Functional Data Analysis Applied to Modeling of Severe Acute Mucositis and Dysphagia Resulting From Head and Neck Radiation Therapy.

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Publication Date
2016-11-15
ICR Author
Dean, Jamie
Harrington, Kevin
Gulliford, Sarah
Author
Dean, JA
Wong, KH
Gay, H
Welsh, LC
Jones, A-B
Schick, U
Oh, JH
Apte, A
Newbold, KL
Bhide, SA
Harrington, KJ
Deasy, JO
Nutting, CM
Gulliford, SL
Type
Journal Article
Metadata
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Abstract
PURPOSE: Current normal tissue complication probability modeling using logistic regression suffers from bias and high uncertainty in the presence of highly correlated radiation therapy (RT) dose data. This hinders robust estimates of dose-response associations and, hence, optimal normal tissue-sparing strategies from being elucidated. Using functional data analysis (FDA) to reduce the dimensionality of the dose data could overcome this limitation. METHODS AND MATERIALS: FDA was applied to modeling of severe acute mucositis and dysphagia resulting from head and neck RT. Functional partial least squares regression (FPLS) and functional principal component analysis were used for dimensionality reduction of the dose-volume histogram data. The reduced dose data were input into functional logistic regression models (functional partial least squares-logistic regression [FPLS-LR] and functional principal component-logistic regression [FPC-LR]) along with clinical data. This approach was compared with penalized logistic regression (PLR) in terms of predictive performance and the significance of treatment covariate-response associations, assessed using bootstrapping. RESULTS: The area under the receiver operating characteristic curve for the PLR, FPC-LR, and FPLS-LR models was 0.65, 0.69, and 0.67, respectively, for mucositis (internal validation) and 0.81, 0.83, and 0.83, respectively, for dysphagia (external validation). The calibration slopes/intercepts for the PLR, FPC-LR, and FPLS-LR models were 1.6/-0.67, 0.45/0.47, and 0.40/0.49, respectively, for mucositis (internal validation) and 2.5/-0.96, 0.79/-0.04, and 0.79/0.00, respectively, for dysphagia (external validation). The bootstrapped odds ratios indicated significant associations between RT dose and severe toxicity in the mucositis and dysphagia FDA models. Cisplatin was significantly associated with severe dysphagia in the FDA models. None of the covariates was significantly associated with severe toxicity in the PLR models. Dose levels greater than approximately 1.0 Gy/fraction were most strongly associated with severe acute mucositis and dysphagia in the FDA models. CONCLUSIONS: FPLS and functional principal component analysis marginally improved predictive performance compared with PLR and provided robust dose-response associations. FDA is recommended for use in normal tissue complication probability modeling.
URL
https://repository.icr.ac.uk/handle/internal/62
Collections
  • Cancer Biology
  • Radiotherapy and Imaging
Licenseref URL
https://creativecommons.org/licenses/by/4.0
Version of record
10.1016/j.ijrobp.2016.08.013
Subject
Acute Disease
Area Under Curve
Carboplatin
Cisplatin
Deglutition Disorders
Dose-Response Relationship, Radiation
Head and Neck Neoplasms
Humans
Models, Statistical
Mucositis
Organs at Risk
Principal Component Analysis
ROC Curve
Radiation Injuries
Radiation-Sensitizing Agents
Radiotherapy Dosage
Regression Analysis
Research team
Clinical Academic Radiotherapy (Horwich)
Radiotherapy Physics Modelling
Targeted Therapy
Language
eng
Date accepted
2016-08-12
License start date
2016-11-15
Citation
Int J Radiat Oncol Biol Phys, 2016, 96 (4), pp. 820 - 831

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