Risk Stratification for Rejection and Infection after Kidney Transplantation.

Cippà, Pietro E; Schiesser, Marc; Ekberg, Henrik; van Gelder, Teun; Mueller, Nicolas J; Cao, Claude A; Fehr, Thomas; Bernasconi, Corrado Angelo (2015). Risk Stratification for Rejection and Infection after Kidney Transplantation. Clinical journal of the American Society of Nephrology, 10(12), pp. 2213-2220. American Society of Nephrology 10.2215/CJN.01790215

Full text not available from this repository.

BACKGROUND AND OBJECTIVES

Definition of individual risk profile is the first step to implement strategies to keep the delicate balance between under- and overimmunosuppression after kidney transplantation.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We used data from the Efficacy Limiting Toxicity Elimination Symphony Study (1190 patients between 2002 and 2004) to model risk of rejection and infection in the first year after kidney transplantation. External validation was performed in a study population from the Fixed-Dose Concentration-Controlled Trial (630 patients between 2003 and 2006).

RESULTS

Despite different temporal dynamics, rejections and severe infections had similar overall incidences in the first year after transplantation (23.4% and 25.5%, respectively), and infections were the principal cause of death (43.2% of all deaths). Recipient older age, deceased donor, higher number of HLA mismatches, and high risk for cytomegalovirus disease were associated with infection; deceased donor, higher number of HLA mismatches, and immunosuppressive therapy including cyclosporin A (compared with tacrolimus), with rejection. These factors were integrated into a two-dimensional risk stratification model, which defined four risk groups: low risk for infection and rejection (30.8%), isolated risk for rejection (36.1%), isolated risk for infection (7.0%), and high risk for infection and rejection (26.1%). In internal validation, this model significantly discriminated the subgroups in terms of composite end point (low risk for infection/rejection, 24.4%; isolated risk for rejection and isolated risk for infection, 31.3%; high risk for infection/rejection, 54.4%; P<0.001), rejection episodes (isolated risk for infection and low risk for infection/rejection, 13.0%; isolated risk for rejection and high risk for infection/rejection, 24.2%; P=0.001), and infection episodes (low risk for infection/rejection and isolated risk for rejection, 12.0%; isolated risk for infection and high risk for infection/rejection, 37.6%; P<0.001). External validation confirmed the applicability of the model to an independent cohort.

CONCLUSIONS

We propose a two-dimensional risk stratification model able to disentangle the individual risk for rejection and infection in the first year after kidney transplantation. This concept can be applied to implement a personalized immunosuppressive and antimicrobial treatment approach.

Item Type:	Journal Article (Original Article)
Division/Institute:	04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology
UniBE Contributor:	Bernasconi, Corrado Angelo
Subjects:	600 Technology > 610 Medicine & health
ISSN:	1555-9041
Publisher:	American Society of Nephrology
Language:	English
Submitter:	Stefanie Hetzenecker
Date Deposited:	11 Jul 2017 14:36
Last Modified:	05 Dec 2022 15:02
Publisher DOI:	10.2215/CJN.01790215
PubMed ID:	26430088
Uncontrolled Keywords:	cause of death; cyclosporin; death; humans; immunosuppression; kidney transplantation; tacrolimus; transplant infectious disease; transplant outcomes; transplant recipients
URI:	https://boris.unibe.ch/id/eprint/94708