Survival analysis Of Patients With end stage renal disease,In The Case Of Adama Hospital Medical Collge.

Abstract

Chronic kidney disease (CKD) with diagonesised end-stage renal disease (ESRD)is common public health problems worldwide. The aim of this study was to model and compare different parametric (Weibull, Log-logistic and Lognormal) and semiparametric (Cox ph) regression survival models, using endstage renal disease (ESRD) data set. Method: This study was conducted from 30, May 2012 to April 1st, 2016 and encompassed 500 ESRD patients at Adama Hospital Medical College. Retrospectives data were gathered by reviewing patients’ medical and surgical wards history. The Cox ph regression and parametric Weibull, Log-logistic and log normal models were used for analyzing survival analysis of ESRD patient using R statistical package and STATA software. To compare these models Akaike Information criterion (AIC) and Cox-Snell residual were utilized. Results: In this study, the totals of 500 ESRD patients were considered. 66.20% were female and 33.80% were male. Among those patients 72.40% and 27.60% were alive and died respectively. Concurrence to the both criteria (AIC and Cox-Snell residual), Lognormal survival model manifested the bestresults as compared with other models. Harmonyto this model, age at the time of admission (HR=0.94, p-value < 0.05), sex of patients (HR=0.54, pvalue <0.05) and Family history (HR=0.45, p-value<0.05), had significant effect on survival of the ESRD patient Conclusion: parametric survival model with baseline hazard lognormal distributionwas found appropriate to our dataset. Deal to the results of study, it conclude that having ESRD with complications increases the probability of death. The estimated survival and hazard rate (time ratio) of ESRD patients under age, sex and Family history had significant difference with p-values less than 0.05. Female patients have greater risk of death than males and based on the mean survival time age of patients greater than 53.34 years have a higher risk of death.