Multivariate Longitudinal Assessment of Kidney Function Outcomes on Graft Survival after Kidney Transplantation Using Multivariate Joint Modeling Approach: A Retrospective Cohort Study

The performance of a transplanted kidney is evaluated by monitoring variations in the value of the most important markers. These markers are measured longitudinally, and their variation is influenced by other factors. The simultaneous use of these markers increases the predictive power of the analytical model. This study aimed to determine the simultaneous longitudinal effect of serum creatinine and blood urea nitrogen (BUN) markers, and other risk factors on allograft survival after kidney transplantation. In a retrospective cohort study, the medical records of 731 renal transplant patients, dated July 2000 to December 2013, from various transplant centers in Mashhad (Iran) were examined. Univariate and multivariate joint models of longitudinal and survival data were used, and the results from both models were compared. The R package joineRML was used to implement joint models. P values <0.05 were considered statistically significant. Results of the multivariate model showed that allograft rejection occurred more frequently in patients with elevated BUN levels (HR=1.68, 95% CI: 1.24-2.27). In contrast, despite a positive correlation between serum creatinine and allograft rejection (HR=1.49, 95% CI: 0.99-2.22), this relationship was not statistically significant. Results of the multivariate model showed that longitudinal measurements of BUN marker play a more important role in the investigation of the allograft rejection.