Normal Tissue Complication Probability (NTCP) Modelling of Severe Acute Mucositis using a Novel Oral Mucosal Surface Organ at Risk.
Clin Oncol (R Coll Radiol)
; 29(4): 263-273, 2017 04.
Article
en En
| MEDLINE
| ID: mdl-28057404
AIMS: 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. MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Radioterapia
/
Mucositis
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Neoplasias de Cabeza y Cuello
/
Mucosa Bucal
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Adolescent
/
Adult
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Aged
/
Aged80
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Humans
/
Middle aged
Idioma:
En
Revista:
Clin Oncol (R Coll Radiol)
Asunto de la revista:
NEOPLASIAS
Año:
2017
Tipo del documento:
Article
Pais de publicación:
Reino Unido