Predicting Xerostomia induced by IMRT treatments: A logistic regression approach


Autoria(s): Soares, Inês; Dias, Joana; Rocha, Humberto; Lopes, Maria do Carmo; Ferreira, Brígida
Data(s)

28/01/2015

28/01/2015

2014

Resumo

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

Identificador

http://hdl.handle.net/10400.22/5501

10.1109/BIBM.2014.6999271

Idioma(s)

eng

Publicador

2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Direitos

openAccess

Palavras-Chave #Radiotherapy #IMRT #logistic regression predictors #ROC curves #AUC
Tipo

conferenceObject