background: although the cox proportional hazard regression is the most popular model for analyzing the prognostic factors on survival of cancer patients, under certain circumstances, parametric models estimate the parameter more efficiently than the cox model.  the aim of this study was to compare the cox regression model  with parametric models in patients with gastric cancer who registered a...

Multivariate adaptive regression splines (MARS) are a useful tool to identify linear and nonlinear effects and interactions between two covariates. In this dissertation a new proposal to model survival type data with MARS is introduced. Martingale and deviance residuals of a Cox PH model are used as response in a common MARS approach to model functional forms of covariate effects as well as pos...

BACKGROUND The pathogenesis of pulmonary hypertension (PH) in hemodialysis is still unclear. The aim of this study was to identify the risk factors associated with the presence of PH in chronic hemodialysis patients and to verify whether these factors might explain the highest mortality among them. METHODS We conducted a retrospective study of hemodialysis patients who started treatment from ...

BACKGROUND Circulating angiopoietin-1 (Ang-1) has been linked to pulmonary hypertension (PH) in experimental studies. However, the clinical relevance of Ang-1 as a biomarker in PH remains unknown. We aimed to investigate the prognostic and clinical significance of Ang-1 in PH using data from the prospectively recruiting Giessen PH Registry. METHODS Patients with suspected PH (without previous...

Missing covariate values is a common problem in a survival data research. The aim of this study is to compare the use of the multiple imputation (MI) and last observation carried forward (LOCF) methods for handling missing covariate values in the Cox proportional hazards (PH) regression model. The comparisons between the methods are based on simulated data. The missingness mechanism is assumed ...

Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...