![](/images/graphics-bg.png)
γ-H2AX : A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer
Joint Authors
Kakolyris, Stylianos
Romanidis, K.
Chatzimichail, E.
Bouros, Demosthenes
Rigas, A.
Matthaios, D.
Papaschinopoulos, Garyfalos
Karakitsos, P.
Source
International Journal of Genomics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-08
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Natural & Life Sciences (Multidisciplinary)
Biology
Abstract EN
Cancer is a leading cause of death worldwide and the prognostic evaluation of cancer patients is of great importance in medical care.
The use of artificial neural networks in prediction problems is well established in human medical literature.
The aim of the current study was to assess the prognostic value of a series of clinical and molecular variables with the addition of γ-H2AX—a new DNA damage response marker—for the prediction of prognosis in patients with early operable non-small cell lung cancer by comparing the γ-H2AX-based artificial network prediction model with the corresponding LR one.
Two prognostic models of 96 patients with 27 input variables were constructed by using the parameter-increasing method in order to compare the predictive accuracy of neural network and logistic regression models.
The quality of the models was evaluated by an independent validation data set of 11 patients.
Neural networks outperformed logistic regression in predicting the patient’s outcome according to the experimental results.
To assess the importance of the two factors p53 and γ-H2AX, models without these two variables were also constructed.
JR and accuracy of these models were lower than those of the models using all input variables, suggesting that these biological markers are very important for optimal performance of the models.
This study indicates that neural networks may represent a potentially more useful decision support tool than conventional statistical methods for predicting the outcome of patients with non-small cell lung cancer and that some molecular markers, such as γ-H2AX, enhance their predictive ability.
American Psychological Association (APA)
Chatzimichail, E.& Matthaios, D.& Bouros, Demosthenes& Karakitsos, P.& Romanidis, K.& Kakolyris, Stylianos…[et al.]. 2014. γ-H2AX : A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer. International Journal of Genomics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-450632
Modern Language Association (MLA)
Chatzimichail, E.…[et al.]. γ-H2AX : A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer. International Journal of Genomics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-450632
American Medical Association (AMA)
Chatzimichail, E.& Matthaios, D.& Bouros, Demosthenes& Karakitsos, P.& Romanidis, K.& Kakolyris, Stylianos…[et al.]. γ-H2AX : A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer. International Journal of Genomics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-450632
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-450632