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Article Model Comparisons of Competing Risk and Recurrent Events for Graft Failure in Renal Transplant Recipients

By Ingar Holme, Bengt C. Fellström, Alan G. Jardine, Anders Hartmann and Hallvard Holdaas


Background and objectives Risk factor analysis of long-term graft survival in kidney transplant recipients is usually based on Cox regression models of time to first occurrence of doubling of serum creatinine or graft loss (DSCGL). However, death is a competing cause of failure, and censoring patients who die could bias estimates. We therefore compared estimates of time to first event versus estimates that included death as a competing risk and recurrent events. Design, setting, participants, & measurementsA Cox regression analysis of 1997–2002 data from the Assessment of Lescol in Renal Transplant (ALERT) trial population identified an eight-factor riskmodel, by analyzing time to first occurrence of DSCGL. The same factors were re-analyzed, allowing for death as competing. The probability of survival free of DSCGL was estimated; and two recurrent models (marginal and conditional) were used for time to events. Results Creatinine, systolic BP, and HLA-DR mismatches lost 33%–46 % of their strength of association with DSCGL when death was included as a competing risk. Small changes were observed if recurrent events were analyzed in the marginal model. Conclusion The relationship between serum creatinine and DSCGL was attenuated when death was considered as a competing risk; inclusion of recurrent events had little effect. These findings have important implications for analysis and trial design in populations at high mortality risk

Year: 2016
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