Introduction to Competing Risk Model In the Epidemiological Research

Background and aims: Chronic kidney disease (CKD) is a public health challenge worldwide, with adverse consequences of kidney failure, cardiovascular disease (CVD), and premature death. Chronic kidney disease leads to the end stage of renal disease (ESRD), if late/not diagnosed. Competing risk modeling is a major issue in Epidemiology research. In Epidemiology study, sometimes inappropriate methods (i.e. Kaplan-Meier method) have been used to estimate probabilities for an event of interest in the presence of competing risks. In these situations, competing risk analysis is preferable to other models in survival analysis studies. The purpose of this study is to describe the bias resulting from the use of standard survival analysis to estimate the survival of a patient with End Stage Renal Disease (ESRD)and to provide alternate statistical methods with consideration of competing risk.Methods: In this retrospective study, 359 patients referred to the hemodialysis department of Shahid Ayatollah Ashrafi Esfahani Hospital, Tehran, Iran, who had undergone continuous hemodialysis for at least three months. Information was collected through patient’s medical history contained in the records, from2011 to 2017. To evaluate the effects of research factors on the the outcome, a cause-specific hazard model and competing risk models were fitted. The data were analyzed using the software stata v14 and SPSS v21 through descriptive and analytical statistics.