Modeling Time-to-First Peritonitis Episode Using Semiparametric Cox and Parametric AFT Survival Models

By : Yehenew G Kifle, Tshepo F. Maja, Ramon A. Tamayo

Page No: 1-16

Abstract
Peritoneal Dialysis (PD) is a process of replacing kidney function that cleans waste product from the blood and removes extra fluid from the body. In most cases, PD process is slowed down by a peritoneal membrane infection called peritonitis, which is the leading cause of morbidity and dialysis failure among PD patients in developing countries. Early prevention of this infection is very crucial for the success of PD in resource-poor countries. Using a prospective study from Pietersburg provincial hospital in South Africa, we have investigated potential social, demographic, and biological risk factors that contribute to the first episode of peritonitis. Both semiparametric Cox proportional hazards and two parametric Accelerated Failure Time (AFT) survival models were fitted to the data and compared for their performance. Weibull AFT model fits better to the peritonitis longitudinal dataset followed by exponential AFT and Cox PH models. Among PD cohort of patients, 60.38% of peritonitis infections were recorded over the follow-up period with the majority of peritonitis infections are recorded among females (65.4%) and rural dwellers (65.7%) with (62.6%) of black Africans which shows a higher risk of developing peritonitis. Patients with no running water and electricity in the house who are living in rural areas with a low level of hemoglobin and shorter duration on PD are associated with a higher risk (hazard) of developing the first episode of peritonitis infections in the study area.

Authors :
Yehenew G Kifle
Department of Mathematics and Statistics, University of Maryland Baltimore County, USA

Tshepo F. Maja
Department of Statistics and Operations Research, University of Limpopo, South Africa

Ramon A. Tamayo
Pietersburg Limpopo Provincial Hospital, South Africa
 

DOI: DOI-https://doi.org/10.32381/IAPQRT.2022.46.01-02.1