On the prediction of Hodgkin lymphoma treatment response
Clin. transl. oncol. (Print)
; 17(8): 612-619, ago. 2015. tab, ilus
Artigo
em Inglês
| IBECS
| ID: ibc-138176
Biblioteca responsável:
ES1.1
Localização: BNCS
ABSTRACT
Purpose. The cure rate in Hodgkin lymphoma is high, but the response along with treatment is still unpredictable and highly variable among patients. Detecting those patients who do not respond to treatment at early stages could bring improvements in their treatment. This research tries to identify the main biological prognostic variables currently gathered at diagnosis and design a simple machine learning methodology to help physicians improve the treatment response assessment. Methods. We carried out a retrospective analysis of the response to treatment of a cohort of 263 Caucasians who were diagnosed with Hodgkin lymphoma in Asturias (Spain). For that purpose, we used a list of 35 clinical and biological variables that are currently measured at diagnosis before any treatment begins. To establish the list of most discriminatory prognostic variables for treatment response, we designed a machine learning approach based on two different feature selection methods (Fishers ratio and maximum percentile distance) and backwards recursive feature elimination using a nearest-neighbor classifier (k-NN). The weights of the k-NN classifier were optimized using different terms of the confusion matrix (true- and false-positive rates) to minimize risk in the decisions. Results and conclusions. We found that the optimum strategy to predict treatment response in Hodgkin lymphoma consists in solving two different binary classification problems, discriminating first if the patient is in progressive disease; if not, then discerning among complete and partial remission. Serum ferritin turned to be the most discriminatory variable in predicting treatment response, followed by alanine aminotransferase and alkaline phosphatase. The importance of these prognostic variables suggests a close relationship between inflammation, iron overload, liver damage and the extension of the disease (AU)
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Coleções:
Bases de dados nacionais
/
Espanha
Base de dados:
IBECS
Assunto principal:
Vimblastina
/
Bleomicina
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Doença de Hodgkin
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Doxorrubicina
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Dacarbazina
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Alanina Transaminase
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Fosfatase Alcalina
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Ferritinas
Tipo de estudo:
Estudo de etiologia
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Estudo de incidência
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Estudo observacional
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Estudo prognóstico
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Fatores de risco
Limite:
Idoso
/
Humanos
Idioma:
Inglês
Revista:
Clin. transl. oncol. (Print)
Ano de publicação:
2015
Tipo de documento:
Artigo
Instituição/País de afiliação:
Hospital Cangas de Narcea/Spain
/
Hospital San Agustin/Spain
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Hospital Universitario Central de Asturias/Spain
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Hospital Valle del Nalon/Spain
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Hospital de Arriondas/Spain
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Hospital de Cabueñes/Spain
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Hospital de Jarrio/Spain
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Hospital de Mieres/Spain
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University of Oviedo/Spain