[Comparison of artificial neural network and parametric regression models in survival prediction of patients with gastric cancer]

ABSTRACT

Using parametric models is common approach in survival analysis. In the recent years, artificial neural network [ANN] models have increasingly used in survival prediction. The aim of this study was to predict of survival rate of patients with gastric cancer by using a parametric regression and ANN models and compare these methods. We used the data of 436 gastric cancer patients from a cancer registry in Tehran between 2002-2007. All patients had a confirmed diagnosis. Data were randomly divided into two groups training and testing [or validation] set. For analysis of data we used a parametric model [exponential, Weibull, normal, lognormal, logistic and log-logistic models] and a three layer ANN model. In order to compare of the prediction of two models, we used the area under receiver operating characteristic [AUROC] curve, classification table and concordance index. The prediction accuracy of the ANN and the parametric [Weibull] models were 79.45% and 73.97% respectively. The AUROC for the ANN and the Weibull models were 0.815 and 0.748 respectively. The ANN had a better predictions than the Weibull model. Thus it is suggested to use of the ANN model survival prediction in field of cancer