BACKGROUND: Identification of the prognostic factors for survival in @entity1 with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. OBJECTIVE: To compare @entity797 's regression model with parametric models for determining the independent factors for predicting adults' and pediatrics' survival after liver transplantation. METHOD: This study was conducted on 183 pediatric @entity1 and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all @entity1 undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, @entity1 class, initial diagnosis of the @entity409 , @entity16900 /MELD score, and pre-operative laboratory markers were selected for survival analysis. RESULT: Among 529 @entity1 , 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric @entity1 . Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and @entity1 class B (HR=2.12, p<0.05) in pediatric @entity1 were the most important factors for prediction of survival after liver transplantation. Adult @entity1 younger than the mean age and pediatric @entity1 weighing above the mean and @entity1 class A (compared to those with classes B or C) had better survival. CONCLUSION: Parametric regression model is a good alternative for the @entity797 's regression model.

Comparison of XXXX 's Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000-2012.

@entity1 :: ('9606', 'Species') :: ['Child', 'patients'] @entity409 :: ('MESH:D008107', 'Disease') :: ['liver disease'] @entity797 :: ('1351', 'Gene') :: ['Cox'] @entity16900 :: ('26580', 'Gene') :: ['PELD']
@entity797 :: (1351,Gene) :: ['Cox']
